Pearl Talent - Data Engineer
RemotePhilippines
Job Summary
Design clean schemas, write efficient SQL, and optimize query performance through indexing and execution-plan analysis for a production Postgres backend powering an applicant tracking system. Extend and evolve the database across recruiting, candidates, and business operations, building SQL views and derived tables as standard interfaces for reporting and AI consumers. Define and enforce PII, data-classification, and retention policies at the database level while managing Git-based schema migrations. This role pairs closely with Engineering and AI Engineering teams as the company scales its database foundation to support AI features. Success in the first 3–6 months includes a completed schema audit, measurable p95 gains on key dashboards, and aligned column-level PII classification.
Required Qualifications
- 3+ years working with production PostgreSQL databases
- Advanced SQL: window functions, CTEs, JSONB, EXPLAIN analysis, and query rewriting for performance
- Relational data modeling for both OLTP and analytical use cases, including materialized views, indexing, and partitioning on OLTP Postgres
- Defining and enforcing PII, data-classification, and retention policies at the database level
- Git-based schema-migration workflows (Flyway, sqitch, or comparable) with PR review
- Basic Python or comparable scripting for one-off data operations and validation
- B2+ English (CEFR) for technical documentation read across teams
Desired Qualifications
- Experience with Supabase (RLS, auth model, Realtime, Storage)
- Experience with dbt or SQLMesh for versioning SQL transformations
- Prior work exposing datasets to AI/ML consumers (feature datasets, embedding indexes, eval sets)
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