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AI-First Data Engineer (m/f/d) at Sport Alliance GmbH. Location Information: . 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 EUR 72,000 – EUR 82,000 per year.. . Final compensation will be based on experience, skills, and overall fit for the role.. . . Your benefits with us. . . 30 Days Annual Leave . with a 5-day workweek– enjoy extra paid time off to rest, recharge, and balance your work and personal life. . Flexible Work Model. – 100% remote work within Germany. . Fitness & Well-being (Choose 1 of 2):. Stay active your way! Choose either our free . Move Republic Program. to earn points for rewards, . OR. join . EGYM Wellpass. for just a €20/month co-pay to access a massive network of gyms, pools, and studios (we cover the rest!). . Access to Udemy . –. . boost your skills with thousands of high-quality online courses. . Deutschland Ticket Subsidy . – commute affordably – we cover part of your ticket cost. . Company Pension Scheme (bAV). – receive an above-average employer contribution in Germany or Austria. . Flexible Working Hours . – adjust your schedule to fit your lifestyle. . Employee Discounts . –. . access top deals in Germany and Austria via our benefits portal. .