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-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).
Your salary
We offer a salary range of PLN 24,000 – PLN 28,000 gross per month (UoP).
Final compensation will be based on experience, skills, and overall fit for the role
Your benefits with us
Benefits package – private medical care and a sports card to support your health and well-being
Access to Udemy Business – boost your skills with thousands of high-quality online courses
Flexible work model – work fully remotely or combine it with on-site collaboration at our modern office in Warsaw
Flexible Working Hours – adjust your schedule to fit your lifestyle
Unique experience in the Fitness and SaaS industry – join a market-leading company in a dynamic, fast-growing industry
International team – work alongside talented colleagues from around the world in a diverse and inclusive environment
Unforgettable company events – take part in engaging team-building activities and memorable celebrations
Sport Alliance GmbH is a FitTech software company driving digital transformation in the fitness industry. Operating with a startup atmosphere and agile mentality, the company is undergoing rapid professionalization and scaling. They are building AI-driven technology solutions for the fitness sector and maintain operational hubs in Hamburg and Warsaw. The company values employee input and is actively integrating AI capabilities into their product and organizational workflows.
