Analytics Engineer
hace 7 días
❗️IMPORTANT : This position is on-site in Valencia, Spain. ❗️We can provide relocation assistance if you’re outside of the city or country. ✅ Requirements Strong understanding of product analytics and event-based tracking; Experience working with databases and analytical warehouses (Snowflake preferred); Strong SQL and Python skills; Solid understanding of data modeling, schemas, and data pipelines; Ability to translate product logic into correct data structures; Experience working closely with frontend, backend, product, and data teams; High attention to detail and strong ownership mindset. Nice to Have Experience in iGaming / gaming / high‑traffic consumer products; Familiarity with tracking tools (GA, BQ, ClickHouse); Experience defining tracking plans or analytics specifications; Basic understanding of ETL / ELT pipelines; Experience working with data architects or analytics platforms. Responsibilities Product & Feature Understanding Analyze how new product features work from a user behavior and product logic perspective; understand feature implementation on both frontend and backend levels to ensure correct tracking logic. Analytics Requirements & Tracking Design Define analytics requirements before feature launch, including events, attributes, and user‑level data to be tracked; naming conventions, schemas, and data structure. Work closely with product managers, frontend and backend engineers to align on tracking implementation; ensure tracking is designed to support future analysis, segmentation, and business questions. Data Quality & Consistency Validate that data written to the database is logically correct and meaningful; prevent incorrect aggregation or data pollution (e.g., different bonus types merged into a single “bonus” field). Identify inconsistencies between product logic and recorded data. End‑to‑End Data Flow Validation Validate the full data pipeline: Frontend → Backend → Database → Snowflake. Ensure no data loss, duplication, or incorrect transformations occur. Collaborate closely with Data Engineers and Data Architects to align tracking with data models; validate transformations and ingestion logic; improve data reliability and scalability. Post‑Launch Monitoring & Support Perform post‑launch data validation and ongoing monitoring; detect and investigate anomalies, missing events, or broken tracking; support insight analysts by ensuring data is clean, consistent, and analysis‑ready. Documentation & Enablement Maintain clear documentation for tracking schemas; metrics definitions; business logic and assumptions. Act as a single point of ownership for tracking and data quality standards. What We Offer 23 days of paid vacation leave; Six additional days of undocumented sick leaves; Medical Insurance; #J-18808-Ljbffr
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