Sport Alliance

Cloud-based gym management and fintech SaaS

AI-First Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Full-timeRemote in PolandPLN24k - PLN28k /mo

About the Job

Requirements

At least 3 years of data engineering experience focused on data warehousing.
Strong SQL and Python skills for data work.
Ability to work with AI tools and review and validate their outputs.
A solid grasp of data architecture and modeling principles, including dimensional modeling, slowly changing dimensions, and incremental patterns, or the drive to deepen that knowledge quickly.
Hands-on experience with dbt on a cloud warehouse.
Working knowledge of relational databases and some exposure to non-relational databases such as DynamoDB and MongoDB.
A track record of debugging difficult data issues and shipping durable fixes.
Excellent written and verbal English.

Responsibilities

Build and optimize cloud-native data pipelines on AWS, including ETL/ELT and supporting infrastructure such as Aurora, Redshift, dbt, Spark/EMR, Airflow, and CDC, using AI tooling as a standard part of the workflow.
Design and evolve data models that power analytics, operational use cases, and AI/ML across thousands of studios.
Improve data reliability by embedding governance, testing, and lineage so people and AI systems can trust the numbers.
Partner with product and other engineering teams to turn ambiguous business problems into robust data solutions.
Evaluate and evolve approaches such as data mesh patterns and emerging AI tooling, and help determine what belongs in the technology stack.
Grow into the financial and regulatory reporting workstream, where correctness and auditability are important.

Desired Qualifications

Experience with AWS, including Redshift, EMR, Glue, S3, or IAM; experience with GCP or Azure is also welcome.
Experience with streaming or CDC technologies such as Kafka, Kinesis, or Debezium, or with data mesh.
Experience building data pipelines for ML or AI systems.
Exposure to financial, payments, or regulated reporting data.
German language skills for some stakeholder work.

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

About the Company

Sport Alliance

Cloud-based gym management and fintech SaaS

Sports Alliance provides a cloud-based software backbone for the fitness industry, serving gyms, large franchises, and chains in Europe. It combines SaaS platforms and fintech features with lead generation to digitalize fitness operations. The core product is a digital infrastructure that gyms use to run daily operations, including studio and member management, scheduling, and payments, via platforms like Magicline for studio management and EuroFit24. How it works: the platform is accessed as a service in the cloud, integrating multiple service platforms to manage memberships, bookings, payments, and business processes, enabling scale across many locations. How it differentiates: it targets the European market and bundles gym-management software with fintech capabilities and lead-generation tools, focusing on scalability for large chains rather than lone studios. Its goal is to help fitness businesses operate more efficiently and grow by digitizing their workflows and payments.

Company size: 201-500
Company stage: Growth Equity (Venture Capital)
Total funding: $165M
Headquarters: Hamburg, Germany
Founded: 2011

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