Middle Data Engineer

Description: Build and scale reliable ETL/ELT processes for user activity data collection and processing. Design cloud data warehouses and analytical architectures using modern data tools (BigQuery, Airflow, Dataform). Ensure high availability, accuracy, and security of data processing; maintain quality standards including data lineage and observability. Collaborate with analytics, backend, and infrastructure teams to transform raw data into product metrics and actionable insights. Requirements: Proficient in Python and SQL; capable of building production-ready solutions and optimizing queries under real load. Practical experience with ETL/ELT orchestration (Airflow, Dataform, or similar). Experience with cloud platforms (GCP, AWS, or Azure). Understanding of data warehousing concepts: dimensional modeling, partitioning, clustering, cost control. 3+ years as a Data Engineer in production environments with real load. Ability to articulate and defend technical solutions, take responsibility for results, and proactively share knowledge. Benefits: Access to the SKELAR Platform, which supports founders with essential functions like Legal, Finance, HR, and IT. Networking opportunities with co-founders and top specialists in the market. Exclusive domain education programs tailored for team members. Impact on social projects through the SKELAR foundation, including support for veterans. Inspiring workspaces with amenities like a gym, climbing wall, and green areas. Daily comfort perks including meals, sports training access, medical insurance, and corporate discounts.