Back
Metro location, common Data Engineer title, and broad skills create moderate competition.
Core data engineering skills are transferable, but identity-graph and AdTech preferences increase domain specificity.
Explicit 8-12 years experience and mandatory data platform, cloud, and identity-resolution skills tighten filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and optimize scalable data pipelines and ETL/ELT workflows handling large, complex datasets.
Develop and maintain foundational data architecture supporting identity resolution and ID graph systems, including ingestion, normalization, matching, and deduplication.
Own end-to-end lifecycle of complex data systems, including design, production deployment, performance optimization, and cross-team collaboration.
8-12+ years of hands-on experience in data engineering or large-scale data processing.
Strong expertise in SQL and relational databases (e.g., Postgres, BigQuery, Redshift) and Python for data processing.
Experience with cloud platforms such as Google Cloud Platform (BigQuery, Dataflow, etc.) and/or AWS (S3, Redshift, EMR, RDS).
Proven experience building production-grade data pipelines and distributed systems with large-scale datasets (hundreds of millions to billions of records).
Experienced in architecting mission-critical data platforms with strong technical decision-making capabilities related to scalability and system design.
Background or familiarity with identity graphs, entity resolution, digital identity, or audience data platforms, preferably in AdTech domain.
Comfortable working independently in fast-paced, remote environments with cross-functional teams, delivering reliable, scalable data solutions.