Principal Data Engineer

📋 Description

• Design, build, and optimize scalable data pipelines and ETL/ELT workflows for large, complex datasets.
• Design and implement foundational data architecture supporting identity resolution and ID graph systems.
• Develop and enhance systems supporting identity resolution and ID graph construction (data ingestion, normalization, matching, and deduplication).
• Process and unify multi-source datasets (cookies, device IDs, behavioral data, third-party and proprietary data).
• Write efficient, testable, and maintainable code using Python and SQL for large-scale data processing.
• Optimize data models, queries, and storage strategies for performance, scalability, and cost efficiency.

🎯 Requirements

• 8-12+ years of hands-on experience in data engineering or large-scale data processing.
• Proven experience building and maintaining production-grade data pipelines and distributed systems.
• Demonstrated experience architecting and delivering large-scale data platforms or mission-critical data systems.
• Strong expertise in: SQL and relational databases (PostgreSQL, BigQuery, Redshift, etc.), Python for data processing and analysis.
• Experience with Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Functions) and/or AWS (S3, Redshift, EMR, RDS).
• Experience with distributed data processing and parallelization techniques.