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.