ANALYTICS ENGINEER
We are looking for an Analytics Engineer to build and own the data infrastructure that powers company-wide decision making. You will design our warehouse architecture, define the metrics that the entire business runs on, and ensure every number our teams see is consistent, trustworthy, and well-explained.
What You'll Do:
Data Warehouse Modeling & Layered Architecture
- Design and build a standardized four-layer warehousearchitecture (ODS / DWD / DWS / ADS) on StarRocks, Hive, and related big-data components
- Model core business dimensions including user, device, campaign, app version, region, and acquisition channel
- Enable layered reuse of detail-level data, aggregated data, and application metrics to support analytics across all business lines
Unified Metrics Framework & Semantic Layer
- Map core business scenarios and build a company-wide standardized metrics framework
- Build and maintain the semantic layer to unify metric definitions, dimension semantics, and business logic
- Own canonical definitions for key metrics — user activity(DAU/WAU/MAU), PV/UV, retention, funnel conversion, campaign GMV, device error rate — including calculation rules, dimensions, and documentation
- Shield business users from underlying warehouse complexity; establish a single source of truth that ends cross-team disagreements over "whose number is right"
End-to-End Data Quality Governance
- Establish data governance mechanisms covering: event-tracking review, data validation, dirty-data cleansing, definition iteration, anomaly monitoring, and alerting
- Continuously reduce the share of invalid and anomalous data; keep pipelines stable, trustworthy, and fully traceable