GCP Senior Data Engineer

Required Skills • Leadership: Experience leading data engineering teams onshore and offshore. This is a lead position, not a senior data engineer position. Candidates without leadership experience will not be considered for this role. • Technical: Proficiency in SQL, Python, Java/Scala, and distributed systems (Spark, Beam). • GCP Expertise: Hands-on with BigQuery, Dataflow, Dataproc, Pub/Sub, Composer (Airflow), and Terraform. • DevOps: Familiarity with CI/CD, Git, and infrastructure-as-code. Nice to Have • GCP Certifications (e.g., Professional Data Engineer). • Experience with real-time processing, Vertex AI, or multi-cloud environments. Key Responsibilities: • Pipeline Development: Build and optimize ETL/ELT pipelines using Dataflow (Apache Beam), Dataproc (Spark), Pub/Sub, and Cloud Functions. • Data Infrastructure: Architect and manage BigQuery, Cloud Storage, and Data Fusion for efficient data ingestion, transformation, and storage. • Team Leadership: Lead a team of 10 engineers, review code, establish data engineering standards, CI/CD, and monitoring (e.g., Cloud Monitoring, Logging). • Performance & Cost: Optimize pipeline performance, query efficiency, and GCP cost management (e.g., slot reservations, partitioning). • Collaboration: Work with data architects, scientists, and analysts to deliver self-service data platforms and support advanced analytics/ML use cases. • Data Quality & Governance: Implement data validation, lineage, and metadata management (e.g., Data Catalog, dbt).