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Metro location and common Data Engineer title raise competition, while GCP lakehouse specialization reduces it.
GCP lakehouse specialization increases domain specificity, though core data engineering skills remain transferable.
Explicit 6+ years plus mandatory GCP, BigQuery, Dataflow and lakehouse skills enforce strict filters.
Design, develop, and support scalable data ingestion and transformation pipelines on Google Cloud Platform (GCP).
Build and optimize modern Lakehouse solutions using Dataflow, Dataform, BigQuery, and Pub/Sub for analytics, reporting, and AI-driven data products.
Collaborate with Data Architects, Data Governance, Analytics Engineers, BI Developers, and Business Teams to deliver reliable, secure, and high-performance data solutions.
6+ years of experience (Senior Data Engineer level).
Strong hands-on expertise with Google Cloud Platform services including BigQuery (advanced optimization and tuning), Dataflow (batch and streaming), Dataform, Pub/Sub, Cloud Storage, Dataplex/Data Catalog, Analytics Hub, Cloud Monitoring & Logging, IAM & Security.
Proficiency in data engineering competencies: batch and streaming data processing, ETL/ELT pipeline design, data ingestion frameworks, CDC and incremental processing, data lakehouse concepts, data modeling and warehousing principles.
Programming skills in Python and advanced SQL; Java or Scala preferred.
Experienced in end-to-end GCP data engineering solutions with operational responsibility for pipeline reliability and performance.
Familiar with Lakehouse architecture and modern event-driven data pipeline frameworks in cloud environments.
Able to work cross-functionally with architectural, governance, analytics, and business teams to deliver secure and optimized data products.