Remote Dev Jobs
33 jobs available
Harnham - Data & Analytics Recruitment · 🇬🇧 Birmingham, United KingdomRemote2w ago
Senior Analytics Consultant (Google Cloud, BigQuery, dbt & Looker) 70,000- 90,000 + Quarterly Bonus + Commission Fully Remote (UK) | Quarterly Brighton Meetups I'm hiring a Senior Analytics Consultant for one of the UK's leading specialist modern data consultancies. This is an opportunity to join a highly respected consultancy focused exclusively on the modern data stack, helping organisations build scalable analytics platforms, semantic lay...
Lemon.io · 🌍 WorldwideRemote3w ago
Are you a talented Senior Data Engineer looking for a remote job that lets you show your skills and get decent compensation? Look no further than Lemon.io — the marketplace that connects you with hand-picked startups in the US and Europe. What we offer: The rate depends on your skills and experience. We've already paid out over $11M to our engineers. No more hunting for clients or negotiating rates — let us handle the business side of things so you can focus on what you do best. We'll manually find the best project for you according to your skills and preferences. Choose a schedule that works best for you. It’s possible to communicate async or minimally overlap within team working hours. We respect your seniority so you can expect no micromanagement or screen trackers. Communicate directly with the clients. Most of them have technical backgrounds. Sounds good, yeah? We will support you from the time you submit the application throughout all cooperation stages. Most of our projects involve working in a fast-paced startup environment. We hope you like it as much as we do. Through our community, we will connect you with the best developers from more than 75 countries. We have several different roles for Data Engineers — please check the details if you're interested. Requirements — Data Engineers: 5+ years of commercial experience as a Data Engineer 2+ years of commercial experience with Azure DevOps is a must 2+ years of commercial experience with Databricks 2+ years of experience with DBT is required Experience with Airflow is a plus Requirements — Data Engineers: 4+ years of commercial experience as a Data Engineer 3+ years of experience with Apache Airflow and 2+ years of experience with Snowflake 3+ years of experience with Python and 1+ year with SQL Experience with AWS/GCP/Microsoft Azure/Snowflake is a must Strong technical skills: as a Senior Data Engineer, you are expected to be able to create projects from scratch and have a deep understanding of application
InstacartRemote1mo ago
Headquarters: United States - Remote We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Commercial Scaled Intelligence (CSI) team is an AI-first team dedicated to delivering actionable commercial insights and scalable automation to drive revenue growth and operational efficiency across the company. The team focuses on intelligence generation, predictive analytics, and workflow automation to enable data-driven decision-making and optimize commercial performance. As an Ads AI Analytics Lead II, you will own the intelligence behind our Ads agents. You will design the Ads semantic/context layer and build vertical AI agents that analyze campaigns, diagnose performance, and recommend actions that improve ROAS, pacing, and partner outcomes. You will partner with Ads GTM, Product, Data Science, and Engineering to ship production agents with measurable lift. About the Job Define Ads ontologies and metrics for c
AzumoRemote1mo ago
Headquarters: Buenos Aires, Argentina URL: http://azumo.com Description Azumo is currently looking for a highly motivated Big Data Engineer to develop and enhance data and analytics infrastructure. The position is FULLY REMOTE based in Latin America . This role will focus on building scalable, reliable, and governed data systems that power analytics, live operations, player insights, publishing intelligence, and business decision-making across gaming ecosystem. The ideal candidate has strong hands-on experience with Databricks , DBT , AWS , scalable ETL pipelines, data governance, and modern analytics engineering practices. Experience supporting gaming, telemetry, live operations, or high-scale analytics environments is strongly preferred. Requirements The Data Engineer will be based remotely. Compensation commensurate with experience and candidate potential. Responsibilities: Design, build, and maintain scalable ETL/ELT pipelines using Databricks and AWS Improve ingestion pipeline quality, reliability, scalability, and governance Develop and optimize core data models and foundational data tables Build analytics-ready datasets to support player insights, publishing analytics, esports analytics, and operational reporting Implement data governance, data quality, lineage, and observability practices Collaborate with product, analytics, engineering, and business stakeholders to support data-driven decision-making Optimize large-scale data processing workflows for performance and cost efficiency Support centralized player data models, viewer analytics, publishing activity systems, and operational metrics Contribute to the unification of fragmented data ecosystems across multiple game teams and organizations Build and maintain reliable orchestration workflows and scheduling systems Participate in architectural discussions around scalability, governance, and data platform modernization Required Skills: Strong experience with Databricks Strong SQL and Python programming exp
Proxify ABRemote2mo ago
Headquarters: Sweden URL: http://career.proxify.io The Role: We are looking for a Senior Data Engineer to architect and scale the data foundations for one of our high-growth client products. The ideal candidate is a Python expert who treats data infrastructure as software, implementing CI/CD, unit testing, and observability into every layer of the modern data stack. You are a perfect candidate if you are growth-oriented, you love what you do, and you enjoy working on new ideas to develop exciting products. What we’re looking for: 5+ years of experience building complex data processing applications using Python (Pandas, PySpark, or Dask). Advanced SQL skills for complex transformations, window functions, and query optimization in cloud warehouses. Deep experience with dbt (data build tool) for managing the T in ELT, including documentation and testing. Proven experience with Apache Airflow, Prefect, or Dagster for managing complex dependency graphs. Hands-on experience with Snowflake, BigQuery, or AWS Redshift. Strong understanding of Dimensional Modeling (Star/Snowflake schema) and Data Vault 2.0. Experience with Git, Docker, and implementing CI/CD for data pipelines. Nice-to-Have: Experience building Real-time Pipelines using Kafka or Flink. Familiarity with Data Contracts and Data Quality frameworks (Great Expectations, Monte Carlo). Knowledge of Vector Databases (Pinecone, Milvus) for AI/LLM applications. Infrastructure as Code (Terraform) experience. Responsibilities: Build and maintain scalable, automated ELT/ETL pipelines that provide a 'single source of truth' for the organization. Implement rigorous automated testing and monitoring to ensure data integrity and reliability. Optimize warehouse storage and compute costs while reducing pipeline latency. Partner with Data Scientists and Product Managers to translate business requirements into technical data models. Promote a 'DataOps' culture within the team, conducting code reviews and sharing best practices. Wh
Sport Alliance GmbH · 🇩🇪 GermanyRemote57y ago
Join Sport Alliance and help build the data platform behind Magicline and Finion, serving thousands of gyms and 10M+ members. You'll tackle real engineering challenges, from high-volume data modeling and cost-efficient warehousing to freshness trade-offs and financial data that has to be exactly right. We're building an AI-first data team. We use cutting-edge LLMs and internal tools to work faster, and we expect you to use and improve them. The platform you build powers our AI and analytics, making clean, reliable, well-modeled data essential. Whether you're an experienced engineer ready to own the platform or a strong mid-level engineer eager to grow into the role, we'd love to hear from you. Your position in our team Build and optimize cloud-native data pipelines on AWS — ETL/ELT and the infrastructure underneath (Aurora, Redshift, dbt, Spark/EMR, Airflow, CDC) — using AI tooling as a standard part of the workflow. Design and evolve the data models that power analytics, operational use cases, and AI/ML across thousands of studios. Help raise the bar on data reliability — embed governance, testing, and lineage so both people and AI systems can trust the numbers by default. Partner with product, and other engineering teams to turn ambiguous business problems into robust data solutions. Evaluate and evolve new approaches with us — data mesh patterns, and emerging AI tooling — and help decide what genuinely earns a place in our stack. Grow into our financial and regulatory reporting workstream (Finion Capital), where correctness and auditability matter most. Your profile 3+ years in data engineering with a focus on data warehousing — and the appetite to take on more ownership than you've held so far. Strong SQL and Python for data work. Working with AI tools feels natural to you — and, just as important, the judgment to review and validate what they produce. You treat AI output as a draft to verify, not an answer to trust, especially where correctness is non-negotiabl
Kestra Technologies · EuropeRemote57y ago
About Kestra At Kestra, we’re on a mission to make orchestration and automation simpler for everyone. Our open-source platform helps teams manage complex workflows with confidence, and we’re already making a big impact in businesses around the world. Now, we’re looking for a Full Stack Engineer to help us take things to the next level. In March 2026, we closed a $25M Series A led by RTP Global, with participation from Alven, ISAI, and Axeleo – backed by founders from Datadog, dbt Labs, and Hugging Face. About the role Kestra orchestrates workflows across systems and domains. AI agents and LLM-driven workflows are a growing part of that, and this role is about making sure they can run reliably inside the orchestrator. This is not a wrapper around a model API, but a platform orchestrating how agent steps should be run, retried, branched, and kept observable inside the orchestrator. That work happens in the Kestra core, which is Java. What you would do Design and build the execution primitives for AI workflows in the Kestra engine Build and maintain the plugins that connect Kestra to LLM providers and agent frameworks Turn real agent use cases into reusable blueprints, together with the product team Keep AI executions observable and debuggable to the same standard as the rest of Kestra What we are looking for A strong Java background. You have built and maintained production Java systems, not used Java in passing. Hands-on experience with LangChain4j or a comparable Java agent framework A clear mental model of how agentic systems are actually run: tool calls, state, retries, failure modes Comfort working close to an orchestration engine, where correctness and reliability matter more than demos Our Tech Stack Backend : Java, Micronaut Frontend : Vue.js, Bootstrap Datastore : Kafka, Elasticsearch, PostgreSQL, MySQL Infrastructure : Docker, Kubernetes, Terraform Cloud : GCP, AWS, Azure Tools : GitHub for repo management, actions, and issues We work with a variety of moder
Kestra Technologies · EuropeRemote57y ago
About Kestra Kestra is the universal orchestration platform: open source, declarative, and designed to orchestrate data pipelines, IT automation, business workflows, and AI/agentic systems. Trusted by over 10,000 organizations worldwide, including JPMorgan Chase, Bloomberg, FILA, and Crédit Agricole, Kestra orchestrates mission critical workloads at scale. The open source project has close to 30,000 GitHub stars, hundreds of contributors, and a rapidly growing global community. In March 2026, we closed a $25M Series A led by RTP Global, with participation from Alven, ISAI, and Axeleo, backed by founders from Datadog, dbt Labs, and Hugging Face. The Role We're looking for a QA Engineer based in India or Europe to ensure the quality and reliability of Kestra's platform across both the open source and Enterprise editions. A key part of this role involves working directly with customer support tickets: understanding reported issues, reproducing them in local or staging environments, and verifying fixes before they ship. You'll be the bridge between what customers experience and what the engineering team delivers. This is a fully remote position. We're hiring from India and Europe for timezone alignment with the broader team. What You'll Do Review and analyze customer support tickets to understand reported issues, extract reproduction steps, and translate problems reported by customers into actionable bug reports for the engineering team. Reproduce bugs reported by customers across different environments and configurations, ensuring the engineering team has the context they need to fix issues efficiently. Design, write, and maintain test plans and test cases covering both the open source platform and Enterprise Edition features. Perform manual and exploratory testing for new features and regression testing for existing functionality across each release cycle. Collaborate with engineers to define acceptance criteria, identify edge cases, and validate fixes before release.
Kestra Technologies · EuropeRemote57y ago
About Kestra Kestra is the universal orchestration platform — open source, declarative, and designed to orchestrate data pipelines, IT automation, business workflows, and AI/agentic systems. Trusted by over 10,000 organizations worldwide — including JPMorgan Chase, Bloomberg, FILA, and Crédit Agricole — Kestra orchestrates mission-critical workloads at scale. The open-source project has close to 30,000 GitHub stars , hundreds of contributors, and a fast-growing global community. In March 2026, we closed a $25M Series A led by RTP Global, with participation from Alven, ISAI, and Axeleo – backed by founders from Datadog, dbt Labs, and Hugging Face. About the role Kestra orchestrates workflows across systems and domains, and AI agents and LLM-driven workflows are a growing part of that. You will own the product side of AI workflows at Kestra: what we build and for whom. The job is to find the AI use cases worth supporting, validate them with customers, and shape them into product. You would work directly with the founders, the engineering team, and customer-facing colleagues. What you will do Define the AI features, from use cases to roadmap planning Run customer and prospect interviews to validate which AI workflows are worth building Turn validated use cases into specs and reusable blueprints with the engineering team Decide what we do not build, and say so clearly What we are looking for Real experience building AI or developer products, with examples you can talk through in depth Strong product judgment: you can tell a serious use case from a flashy one Technical fluency. You do not need to write the code, but you need to understand agents, orchestration, and integrations well enough to scope them. Direct, low-fluff communication Perks & Benefits Work from anywhere: We’re a remote-first company, so you can work from wherever feels like home. Plus, you’ll have access to coworking spaces worldwide if you ever need a change of scenery. Health coverage: From medical su
caronsale · 🇩🇪 Berlin, GermanyRemote57y ago
<h1>Senior Machine Learning Engineer (m/w/d)</h1> <p>Four models in production today. Fifteen to twenty by mid-2027. The shared pipeline that gets them there has to hold — and you own everything after handoff: packaging, deployment, drift detection, and the call on whether a model is fit to serve.</p> <p><strong>Location:</strong> Berlin Schöneberg — you work from our office, hybrid with 3 days office and 2 days home office.</p> <h3>About us</h3> <p>CarOnSale is the AI-powered platform for B2B used car trading in Europe. Over 40,000 buyers from more than 20 countries trade on our platform — and 85% of inventory is exclusive to us. We connect software, pricing intelligence, logistics and financing in one layer — as the operating system for an entire industry.</p> <p><em><strong>One Platform. One Profit Engine.</strong></em></p> <h3>The platform you build in</h3> <p>Our machine learning runs on one shared, central platform — not a separate pipeline per model. Five canonical stages: data extraction, validation, transformation, training and evaluation. A Snowflake data warehouse feeds a SageMaker managed feature store, and models reach production through governed CI/CD promotion lanes on Terraform-managed AWS infrastructure. Your job is to build inside it and make it stronger, so the next model costs less to ship than the last one.</p> <h3>Your responsibilities</h3> <ul> <li>You own models from handoff through to production: packaging, deployment, monitoring, and the decision on whether a model is ready to serve</li> <li>You keep production models reliable — drift detection, performance monitoring, alerting and incident response when something moves</li> <li>You own the serving and inference path: fitted pipeline artifacts, inference entry points, monitoring hooks and feature-store parity</li> <li>You review model design and evaluation methodology before anything ships, and catch data leakage, backward-window errors and weak evaluation during development, while they are
Lendable · 🇬🇧 London, United KingdomRemote57y ago
About Lendable Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world’s leading fintech companies and are off to a strong start: One of the UK’s newest unicorns with a team of just over 700 people Among the fastest-growing tech companies in the UK Profitable since 2017 Backed by top investors including Balderton Capital and Goldman Sachs Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot ) So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance . We get money into our customers’ hands in minutes instead of days. We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes. Join us if you want to Take ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1 Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo Build the best technology in-house , using new data sources, machine learning and AI to make machines do the heavy lifting About the role We're looking for an analytics engineer to contribute to the analytical foundation of the UK Cards team, a growing area of the business. You’ll work closely with analysts, product teams, backend engineers, and business stakeholders to improve how data is structured, transformed, and consumed across the company. The role is fundamentally about building a strong analytical foundation: making it easier for teams to move from question to insight quickly, while maintaining high standards around data quality, scalability, and maintainability. You'll contribute to the modelling layer, help improve how the business work wi
Pleo · 🇬🇧 United KingdomRemote57y ago
About Pleo Messy spend management is tricky business. And tedious processes are a lose-lose situation for all involved, not just finance. At Pleo, we're changing that. We build spend solutions that make managing money seamless, empowering, and surprisingly effective for finance teams and employees alike - with a vision to help all businesses ‘go beyond’. The word ‘Pleo’ actually means ‘more than you’d expect’, and living by that mantra has been the secret to our success over the last 10 years. Now, we’re at a pivotal moment in our journey; every move we make has a direct impact on our 40,000+ customers, our business, and our collective success. We need people who take pride in uncovering customer needs, who turn complex problems into simple solutions, challenge the way things are done (respectfully), and always aim high. With great ambitions driving us forward, we can’t say we’ve got this whole thing figured out. And frankly, that’s half the fun! What we can say is that we’re a driven, progressive, and, importantly, a kind bunch of 850+ people from over 100 nationalities, all committed to delivering the future of business spending, together. About the role Pleo's Intelligence function covers the full analytical picture - product behaviour, GTM performance, commercial data science, financial reporting, and operational intelligence. The Analytics Engineers who serve these teams own the data modelling layer that all of it runs on: dbt models, metric definitions, and semantic layer contributions that analysts, product teams, and AI tools depend on to get consistent, trustworthy answers. You'll be embedded in the Product Intelligence team, building the tracking, experimentation, and data modelling foundations that make product data trustworthy and self-serve. You'll join a close-knit team actively migrating our analytics stack onto a new Analytics Warehouse and Omni, moving off legacy tools like Looker and Hippocampus. If you want to build the infrastructure that other p
SoSafe · 🇬🇧 United KingdomRemote57y ago
SoSafe has the ambition to become the leading human risk management provider in Europe. Our award-winning awareness platform triggers behavioural change by providing effective and engaging training and simulations on cybersecurity and data protection. Cybercrime is costing the world >$10 trillion annually and growing by 15% p.a. - we invite you to be part of the solution!" Location: UK, Ireland, or Portugal. Candidates must have work authorization in one of these countries. Office access available in London, Dublin, and Lisbon. Here's how you'll make a difference: Own the transformation layer in dbt - design, build, and maintain modular, well-tested data models that define how data is structured and consumed across the company. Define and implement core business metrics (e.g. activation, engagement, retention) as reusable, versioned data assets- ensuring consistent definitions across analytics, product, and AI use cases. Model complex SaaS data by integrating product events, CRM (Salesforce), and support data into clean, well-defined fact and dimension models. Build and evolve our semantic layer - creating a reliable abstraction over our data that enables consistent KPI definitions and supports downstream consumers, including LLM-based analytics agents. Collaborate with Data Engineers on upstream data contracts and event schemas - ensuring raw data is structured in a way that supports scalable, reliable analytics. Establish and enforce best practices in testing, documentation, and data quality- making these part of the standard development lifecycle. Document models, metrics, and lineage clearly - enabling self-service and reducing ambiguity across teams. What you bring: 5+ years in analytics engineering or data engineering with a strong focus on data modeling Strong proficiency in dbt and SQL- building modular, well-tested models Solid understanding of dimensional modeling and metric design Experience working with cloud data warehouses (BigQuery, Snowflake, or Reds
Eraneos · 🇩🇪 Hamburg, GermanyRemote57y ago
Das findest Du bei uns Wir sind ein technisches, umsetzungsorientiertes Spin-Off einer global agierenden Managementberatung. Zu unseren Kunden gehören primär DAX und Fortune Global 500 Unternehmen, die wir zu Fragen in den Bereichen Analytics, Big Data und Machine Learning beraten. Wir übernehmen in der Gruppe die Entwicklung von individuellen und datengetriebenen Lösungen, um so unsere Kunden in KI-gestützte Unternehmen zu transformieren. Wir bieten ein internationales Arbeitsumfeld mit agilen Teams und kreativen Startup-Methoden sowie eine überdurchschnittliche Vergütung und zahlreiche Zusatzleistungen. Mit unserem HQ in Hamburg, weiteren Büros in München und Düsseldorf sowie unseren Hub-Standorten in allen weiteren deutschen Großstädten (Köln, Berlin, Frankfurt und Stuttgart) stellen wir sicher, dass alle Kollegen deutschlandweit in unser Expertenteam eingebunden sind. Als Senior Analytics Engineer übernimmst Du eine zentrale Rolle in der Konzeption und Umsetzung moderner Analytics-Lösungen. Gemeinsam mit unseren Kund:innen entwickelst Du skalierbare Datenmodelle und Analytics-Architekturen, die eine verlässliche Grundlage für Reporting, Self-Service Analytics und datengetriebene Entscheidungen schaffen. Du konzipierst, entwickelst und verantwortest analytische Datenmodelle auf modernen Data Warehouses und Data Lakehouses und stellst deren Qualität, Performance und nachhaltige Weiterentwicklung sicher. Du entwickelst robuste Datentransformationsprozesse mit dbt und etablierst Best Practices für Testing, Dokumentation, Versionierung und Deployment. Du entwirfst skalierbare analytische Datenmodelle auf Basis etablierter Modellierungsansätze wie Kimball, Snowflake Schema oder Data Vault 2.0 und integrierst unterschiedlichste Datenquellen zu einer konsistenten Analytics-Landschaft. Du etablierst und verantwortest Konzepte für Data Quality, Data Testing, Data Lineage und Data Governance und unterstützt den Aufbau moderner Analytics-Standards. Du optimierst Datenmodell
Recare Deutschland GmbH · JobRemote57y ago
About Recare As one of the leading German HealthTech companies, we are reshaping discharge management – technology-driven, patient-centered, and free from bureaucracy. In addition to our market-leading SaaS platform, we develop AI solutions that radically simplify processes in hospitals and for aftercare providers, relieve healthcare professionals, and refocus attention on patients. Today, we already connect two-thirds of all German hospitals with over 650 rehabilitation clinics and 25,000 nursing and homecare providers. With currently around 100 employees, we continue to grow – and we are looking for people with character who want to help us improve the healthcare system and solve administrative complexity across care journeys in Europe. What to expect as our Senior AI Data Platform Engineer (m/w/d): Purposeful work – your role will have a positive impact on patients, their families, and healthcare professionals. Company culture – we believe in flat hierarchies that promote high performance and strong team dynamics. We foster an environment characterized by mutual respect, loyalty, and recognition. Together, we strive for our goals – and expect the same from you. Flexibility – want to pick up your child from daycare? Like to exercise during lunch? We’ll support you. We are a remote-friendly company offering flexible working hours. Workations are also possible by arrangement. Edenred card – which you can use according to your needs. Extra vacation day – so you can celebrate your birthday with your loved ones, you’ll have the day off. In this role, you can make an impact and grow with us as Senior AI Data Platform Engineer (m/w/d): You will own and evolve the data backbone that powers Recare’s AI products (Voice, Extract & Docs, Agent) and the shared platform primitives that agentic systems depend on. Your work ensures that data ingestion, processing, and serving are reliable, secure, and production-ready - forming the foundation for scalable AI systems in healthcare
Lendable · 🇬🇧 London, United KingdomRemote57y ago
About Lendable Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world’s leading fintech companies and are off to a strong start: One of the UK’s newest unicorns with a team of just over 700 people Among the fastest-growing tech companies in the UK Profitable since 2017 Backed by top investors including Balderton Capital and Goldman Sachs Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot ) So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance . We get money into our customers’ hands in minutes instead of days. We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes. Join us if you want to Take ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1 Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo Build the best technology in-house , using new data sources, machine learning and AI to make machines do the heavy lifting We're looking for a Senior Analytics Engineer to support building the analytical foundation for our US Loans team, the fastest-growing area of the business. In this role, you’ll work closely with analysts, product teams, backend engineers, and business stakeholders to improve how data is structured, transformed, and consumed across the company. The role is fundamentally about building a strong analytical foundation: making it easier for teams to move from question to insight quickly, while maintaining high standards around data quality, scalability, and maintainability. You’ll operate with a high degree of ownership, helping shap
Primer.io · 🇬🇧 United KingdomRemote57y ago
An Introduction to Primer Primer is the unified infrastructure for global payments. We give finance and payments teams the visibility and control to reduce complexity, improve performance, and capture more revenue - all from a single platform. Backed by Sofina, Peak XV Partners, ICONIQ, Tencent, Accel, and Balderton, we're building the payments layer the world's best companies rely on. Watch our showcase > Read up on our $100m Series C Learn more about our culture > Which team will you be joining? Every payment that flows through Primer generates data, and the Data team is what turns that torrent into something merchants and the business can actually use. We build and operate the data platform behind Primer's unified payments infrastructure, the event streaming architecture powering real-time payments analytics, the data lakehouse that makes payments data trustworthy and queryable at scale, and the pipelines that feed everything from merchant-facing insights to internal decision-making. The team is small and senior - a tight group of data engineers, including Staff-level talent, operating with a high degree of autonomy. Alongside it sits Primer's emerging ML function, which will fold into this role's remit as it matures. You'll lead the Data team as its Engineering Manager owning delivery, growth, and technical direction, reporting into a Senior Engineering Manager and partnering closely with Product and other teams across engineering, finance and revenue operations. What will you be doing? Own delivery end to end across the data platform: streaming, warehousing, modelling, and the pipelines in between, holding the team to a consistent bar on quality and pace without becoming the bottleneck yourself Lead, coach, and grow the engineers on your team: career development, feedback, performance, and building an environment where the team does its best work Stay technically credible. You'll review designs for real-time streaming systems, evaluate trade-offs in warehouse a
Bikeleasing · 🇩🇪 GermanyRemote57y ago
Deine Aufgaben Mit der Bikeleasing Gruppe gestalten wir die Zukunft moderner Mobilität und Arbeitswelten. Als führende Unternehmensgruppe für Arbeitgeber-Benefits und Mobilitätslösungen vereinen wir fünf spezialisierte Unternehmen unter einem Dach – von Multi-Benefit-Anbietern über Leasing- und Versicherungsdienstleister bis hin zu Händlern für refurbished Bikes. Wir wachsen profitabel und befinden uns auf einer spannenden technischen Transformationsreise. Als Team Lead Data Products & Analytics (gn) hast Du maßgeblichen Einfluss darauf, wie wir Daten in echten Business-Mehrwert verwandeln. Du führst ein cross-funktionales Analytics-Team, baust die Team-Lead-Funktion von Grund auf auf und verbindest strategische Datenanforderungen mit operativer Exzellenz. Dich erwartet ein moderner Stack, direkte Linie zum Head of Data und gruppenweite Wirkung über Bikeleasing-Service, Probonio und Bike2Future. Wenn Du Verantwortung übernehmen möchtest, Dinge pragmatisch voranbringst und in einem professionellen Umfeld mit kurzen Entscheidungswegen arbeiten willst – dann sollten wir uns kennenlernen. Du führst disziplinarisch und fachlich ein Team aus Analytics Engineers und Analysten und entwickelst jeden Einzelnen gezielt in seiner Karriere weiter Du ownst den Team-Backlog: Du priorisierst Stakeholder-Anfragen, schützt Teamkapazität und kommunizierst Entscheidungen transparent nach außen Qualität und Weiterentwicklung unserer Datenprodukte treibst Du voran – von KPI-Definitionen und Self-Service-Dashboards über semantische Schichten bis hin zu AI-Produkten Du baust schlanke Prozesse für Refinement, Planung und Delivery auf und hältst Overhead konsequent klein Du arbeitest eng mit dem Head of Data und technischen Peers zusammen, übersetzt Prioritäten in konkrete Teamziele und vertrittst das Data-Team in Abstimmungen mit Marketing, Sales und Product Deine Stärken Du hast mehrere Jahre im Analytics- oder BI-Umfeld gearbeitet und bereits ein Team oder Teams fachlich oder disziplinari
Jobrad Loop · 🇩🇪 Munich, GermanyRemote57y ago
Lust auf eine besondere Herausforderung? Du möchtest als Senior Data Engineer nicht bei null anfangen, sondern eine bestehende Data Platform gezielt weiterentwickeln und nachhaltig prägen? Bei uns ist Data mehr als ein Trend – wir machen Daten zu einem echten Erfolgsfaktor. Unsere Datenlandschaft bildet bereits eine starke Grundlage, die wir gemeinsam mit dir technologisch weiterentwickeln und skalieren möchten. Mit deiner Expertise entwickelst du moderne Data Pipelines , skalierbare Data Architekturen und leistungsfähige Lösungen auf Basis von Snowflake . Als Senior setzt du fachliche Impulse, übernimmst eine Mentor:innenrolle und unterstützt dein Team dabei, gemeinsam die nächste Stufe im Data Engineering zu erreichen. Let's ride together! Was du brauchst, um erfolgreich zu sein Fundierte Erfahrung: Du verfügst über mehrjährige Berufserfahrung (mind. 5-7 Jahre) im Data Engineering und hast bereits komplexe Datenplattformen sowie skalierbare Datenlösungen erfolgreich umgesetzt Snowflake-Expertise: Du bringst fundierte Praxiserfahrung mit Snowflake mit und verfügst über ein gutes Verständnis moderner Datenarchitekturen, Performance-Optimierung und Best Practices Technisches Know-how: Du beherrschst SQL und Python sicher und hast idealerweise Erfahrung mit Tools wie dbt , Apache Airflow oder Dagster sowie Cloud-Technologien, vorzugsweise Azure Data-Engineering-Kompetenz: Du kennst dich mit dem Aufbau und Betrieb von ETL-/ELT-Pipelines , Datenmodellierung sowie Data Warehouses und Data Lakes aus Architektur & Qualität: Du verfügst über ein gutes Verständnis für skalierbare Datenarchitekturen und legst Wert auf stabile, performante und wartbare Lösungen Seniorität & Zusammenarbeit: Du überzeugst durch Eigenverantwortung, technisches Urteilsvermögen und die Fähigkeit, dein Wissen als fachliche:r Sparringspartner:in weiterzugeben Kommunikation: Du kommunizierst sicher auf Deutsch und verfügst über gute Englischkenntnisse Dein Beitrag zu unserer Erfolgsgeschichte Unsere D
Bikeleasing-Service GmbH & Co. KG · 🇩🇪 Berlin, GermanyRemote57y ago
Deine Aufgaben Mit der Bikeleasing Gruppe gestalten wir die Zukunft moderner Mobilität und Arbeitswelten. Als führende Unternehmensgruppe für Arbeitgeber-Benefits und Mobilitätslösungen vereinen wir fünf spezialisierte Unternehmen unter einem Dach – von Multi-Benefit-Anbietern über Leasing- und Versicherungsdienstleister bis hin zu Händlern für refurbished Bikes. Wir wachsen profitabel und befinden uns auf einer spannenden technischen Transformationsreise. Als Team Lead Data Products & Analytics (gn) hast Du maßgeblichen Einfluss darauf, wie wir Daten in echten Business-Mehrwert verwandeln. Du führst ein cross-funktionales Analytics-Team, baust die Team-Lead-Funktion von Grund auf auf und verbindest strategische Datenanforderungen mit operativer Exzellenz. Dich erwartet ein moderner Stack, direkte Linie zum Head of Data und gruppenweite Wirkung über Bikeleasing-Service, Probonio und Bike2Future. Wenn Du Verantwortung übernehmen möchtest, Dinge pragmatisch voranbringst und in einem professionellen Umfeld mit kurzen Entscheidungswegen arbeiten willst – dann sollten wir uns kennenlernen. Du führst disziplinarisch und fachlich ein Team aus Analytics Engineers und Analysten und entwickelst jeden Einzelnen gezielt in seiner Karriere weiter Du ownst den Team-Backlog: Du priorisierst Stakeholder-Anfragen, schützt Teamkapazität und kommunizierst Entscheidungen transparent nach außen Qualität und Weiterentwicklung unserer Datenprodukte treibst Du voran – von KPI-Definitionen und Self-Service-Dashboards über semantische Schichten bis hin zu AI-Produkten Du baust schlanke Prozesse für Refinement, Planung und Delivery auf und hältst Overhead konsequent klein Du arbeitest eng mit dem Head of Data und technischen Peers zusammen, übersetzt Prioritäten in konkrete Teamziele und vertrittst das Data-Team in Abstimmungen mit Marketing, Sales und Product Deine Stärken Du hast mehrere Jahre im Analytics- oder BI-Umfeld gearbeitet und bereits ein Team oder Teams fachlich oder disziplinari