AI-First Data Engineer

Join the team building the data platform behind Magicline and Finion, serving thousands of gyms and more than 10 million members. Tackle engineering challenges including high-volume data modeling, cost-efficient warehousing, data-freshness trade-offs, and highly accurate financial data.

The team is building an AI-first data organization, using LLMs and internal tools to work faster. The platform supports AI and analytics, making clean, reliable, and well-modeled data essential.

Whether you are an experienced engineer ready to own the platform or a strong mid-level engineer eager to grow into the role, you are encouraged to apply.

Your position in our team

• Build and optimize cloud-native data pipelines on AWS, including ETL/ELT and underlying infrastructure: Aurora, Redshift, dbt, Spark/EMR, Airflow, and CDC. Use AI tooling as a standard part of the workflow.
• Design and evolve data models powering 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 by default.
• Partner with product and engineering teams to turn ambiguous business problems into robust data solutions.
• Evaluate and evolve approaches such as data mesh patterns and emerging AI tooling, helping determine what belongs in the technology stack.
• Grow into financial and regulatory reporting work for Finion Capital, where correctness and auditability are critical.

Your profile

• 3+ years in data engineering focused on data warehousing, with an appetite to take on increased ownership.
• Strong SQL and Python for data work.
• Comfortable working with AI tools, with the judgment to review and validate their output. Treat AI output as a draft to verify, especially when correctness is non-negotiable.
• Solid understanding of data architecture and modeling principles, including dimensional modeling, slowly changing dimensions, and incremental patterns, or the drive to deepen this knowledge quickly.
• Hands-on experience with dbt on a cloud warehouse.
• Working knowledge of relational databases and exposure to non-relational databases, including DynamoDB and MongoDB.
• Track record of debugging difficult data issues and delivering durable fixes.
• Excellent written and verbal English.

Nice to have

• AWS experience with Redshift, EMR, Glue, S3, and IAM; GCP or Azure experience is also welcome.
• Experience with streaming/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 are helpful for some stakeholder work but not required.

Benefits

• Benefits package including private medical care and a sports card.
• Access to Udemy Business courses.
• Flexible work model: fully remote work or a combination of remote and on-site collaboration at the Warsaw office.
• Flexible working hours.
• Experience in the fitness and SaaS industry.
• International, diverse, and inclusive team.
• Company events, team-building activities, and celebrations.