You own the data lifecycle from ingestion to delivery.
You hand off clean, documented data to the platform engineering team.
You own the budget for the data function (vendors, infrastructure, tooling).
Build and maintain crawlers, API integrations, and vendor data feeds.
Monitor collection reliability.
Onboard new data sources within planned timelines.
Manage the full pipeline (from raw to production).
Implement automated QA at every stage.
Maintain schema integrity in BigQuery (primary), PostgreSQL, and regional databases (China).
Ensure downstream consumers — including the MCP/AI layer — receive consistent, queryable, documented datasets.
Document every transformation rule, edge case, and business logic decision.

Technical SQL fluency (BigQuery preferred)
Python for pipeline orchestration, transformation, and validation
Data modelling and schema design for multi-source, multi-market datasets
Web scraping, crawler development, and API integrations
Entity resolution and deduplication across heterogeneous data sources
Working knowledge of AI/LLM tooling (Claude Code, Copilot, or equivalent)
You take full ownership of your scope and drive it independently
You identify gaps in pipeline coverage and close them systematically
You document thoroughly because undocumented systems are unreliable systems
You treat data quality as non-negotiable — you’ve been burned by bad data before and it shows

Head of Data

Key skills