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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # engineer python sql aws architecture - **Company:** Sport Alliance GmbH - **Location:** Munster, Germany (Remote available) - **Experience:** Expert - **Salary:** €72,000.0 - €82,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Systems, Data Warehousing, Software Debugging, Dimensional Modeling, Amazon DynamoDB, Identity and Access Management, MongoDB, Standard Sql, Data Streaming, Large Language Models, Apache Spark, Debezium, Apache Kafka, Non-relational Database, Data Pipelines - **Published:** July 17, 2026 - **Apply:** https://www.workingnomads.com/job/go/1733463/ ## About the Role * 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-negotiable. * A solid grasp of data architecture and modeling principles (dimensional modeling, slowly-changing dimensions, incremental patterns) - or the drive to deepen it fast. * Hands-on experience with dbt on a cloud warehouse - this is where you'll live day to day. * Working knowledge of relational and some exposure to non-relational Databases (DynamoDB, MongoDB). * A track record of debugging tricky data issues and shipping durable fixes. * Excellent written and verbal English. Nice to have * AWS experience (Redshift, EMR, Glue, S3, IAM); experience with GCP or Azure is also welcome. * Streaming/CDC technologies (Kafka, Kinesis, Debezium) or data mesh. * Experience building data pipelines for ML or AI systems. * Exposure to financial, payments, or regulated reporting data. * German (helpful for some stakeholder work, but not required). ## Description 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Python-Based Data Streaming Pipelines Within Minutes](https://www.wearedevelopers.com/videos/1233-python-based-data-streaming-pipelines-within-minutes) - [40 Minutes to Build a Serverless COVID-19 REST and GraphQL APIs](https://www.wearedevelopers.com/videos/208-40-minutes-to-build-a-serverless-covid-19-rest-and-graphql-apis) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Backend Developer Salary in Germany [2023]](https://www.wearedevelopers.com/magazine/196-backend-developer-salary-in-germany-2023) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)