Principal Data Engineer

📋 Description Design, build, and optimize scalable data pipelines and ETL/ELT workflows for large datasets. Design and implement foundational data architecture supporting identity resolution and ID graphs. Develop identity resolution and ID graph construction (ingestion, normalization, matching). Process and unify multi-source datasets (cookies, device IDs, behavioral data). Write efficient Python and SQL code for large-scale data processing. Optimize data models, queries, and storage for performance, scalability, and cost. 🎯 Requirements 8-12+ years of hands-on experience in data engineering or large-scale data processing. Proven experience building production-grade data pipelines and distributed systems. Strong expertise in SQL and relational databases (Postgres, BigQuery, Redshift) and Python. Experience with GCP (BigQuery, Dataflow, Pub/Sub) and/or AWS (S3, Redshift, EMR, RDS). Experience with large-scale datasets (hundreds of millions to billions of records). Familiarity with CI/CD, Docker, Kubernetes, GitHub Actions.