MABASA / LINKEDIN
Analytics Engineer
Momcozy
- Location
- Singapore, Singapore
- Work type
- fulltime
- Source publication date
- Original publication date not confirmed
- Source closing date
- Not supplied — check original advert
Job description from the source
Location: Singapore Employment Type: Full\-time Department: App Ecosystem Center — Platform Product Group, Data Product Team Role Overview We are looking for an Analytics Engineer to build and own the data infrastructure that powers company\-wide decision making. This role works with de\-identified app data and serves markets outside of China, ensuring every number our teams see is consistent, trustworthy, and well\-explained. You will design our warehouse architecture, define the metrics that the entire business runs on, and establish a single source of truth that ends cross\-team disagreements over “whose number is right.” Who You'll Work With • Reports to: Data Product Lead (China HQ) or Regional Tech Lead • Collaborates with: Product managers, operations teams, customer support, data engineering team (HQ), and regional engineering teams • Team context: Bridges business stakeholders and engineering; works across regions with China HQ data platform team Responsibilities • Design and build a standardized four\-layer warehouse architecture (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, enabling layered reuse of detail\-level data, aggregated data, and application metrics • Map core business scenarios and build a company\-wide standardized metrics framework; 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 • Build and maintain the semantic layer to unify metric definitions, dimension semantics, and business logic, shielding business users from underlying warehouse complexity • Establish end\-to\-end 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 Requirements • Bachelor's degree or above in Statistics, Data Science, Computer Science, Mathematics, or a related field, or equivalent industry experience • 3\+ years of experience in data platform, analytics engineering, or data science at internet companies • Proven ability to build a business data system from 0 to 1, covering the full lifecycle: tracking plan design → event dictionary → dimensional modeling → semantic layer → metrics framework → data governance • Hands\-on experience abstracting business semantics, unifying dimensions, and driving metric standardization to production • Legally authorized to work in Singapore; this role does not provide visa sponsorship
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