← All Positions
Posted Feb 24, 2026

PostgreSQL Database Engineer – AdTech Data Warehouse Implementation

Apply Now
Contract · Remote (US Only) Approx. 15–25 hours per week (with potential to scale during implementation phases) Project Overview We are seeking an experienced PostgreSQL Database Engineer to implement a master-table data consolidation project for a multi-platform AdTech operation. All architecture and design work is complete. You will be executing against comprehensive documentation (4,800+ lines) that includes: Draft SQL queriesDDL scriptsStep-by-step implementation guidesDefined field mappings for master tablesThis is a hands-on implementation role focused on performance, data integrity, and scalability. Current State 13 source tables across Google Ads, Facebook Ads, Amazon, Shopify, and user tracking~11.8M total rows, 262 columnsManual data ingestion (currently via Slack)Slow query performance (5–10 seconds due to complex joins)No unified product naming across systems Target State 6 consolidated master tables spanning all platformsAutomated nightly ETL (no manual ingestion)Sub-second query performance (1s; 10–50x improvement)Unified product catalogMulti-touch attribution tracking capability Technical Requirements Must Have 5+ years PostgreSQL experience in production environmentsExpert-level SQL (complex JOINs, CTEs, window functions, JSONB)ETL pipeline experience (batch processing, incremental loads)Proven experience with large datasets (millions of rows, query optimization)Data integrity validation (QA, reconciliation, testing)AdTech or eCommerce data experience (Google Ads, Facebook, Amazon, Shopify)Must be a U.S. citizen (ITAR requirement)Strong Plus Multi-platform data consolidation experienceAttribution modeling knowledge (first-touch, last-touch, multi-touch)Marketing analytics familiarity (ROAS, CPA, CAC, LTV)DBT (Data Build Tool) experienceAirflow or similar orchestration toolsNice to Have Python for ETL scriptingExperience working with Shopify / Google Ads / Facebook APIsData warehouse modeling (Kimball, dimensional modeling)Advanced indexing and performance-tuning strategies Time Commitment 15–25 hours per weekFlexible schedulePotential for increased hours during key implementation milestones