We're Hiring | GCP Data Engineer | Pan India | TS
We are looking for experienced GCP Data Engineers to join our growing team. The ideal candidate should have robust hands-on experience in Big Query-based data warehousing, Dataproc/Spark processing, and orchestrated, cost-efficient pipelines to deliver scalable analytics and AI-ready data products for BFSI clients.
Location
Pan India
Experience
6–10 Years (role-dependent), including 3+ years hands-on GCP
Employment Type
Full-time
Key Responsibilities
Strong experience and understanding of Data Warehouse and Data Lake platform architecture and design. Design and develop scalable batch and streaming pipelines on GCP using Dataflow, Dataproc (Spark), Pub/Sub, and Cloud Functions. Build and optimise cloud data warehouse solutions on Big Query, including partitioning, clustering, and query cost optimisation. Migrate and modernise legacy workloads (Hadoop, Teradata, on-prem ETL) to GCP using Dataproc, Big Query, and Data Fusion. Develop ELT/ETL workflows with Python, Java, Scala,



and Py Spark; orchestrate pipelines using Cloud Composer (Airflow). Implement data security and governance via Cloud IAM, and build reusable data validation and reconciliation frameworks. Tune Spark and Big Query workloads for performance and cost, achieving measurable runtime and storage improvements. Set up CI/CD and automation for GCP data assets using Git-based pipelines and infrastructure-as-code. Collaborate with architects and client teams on solutioning, Po Cs, demos, and production cutover. Mandatory Skills
Google Cloud Platform (Big Query, Dataproc, Dataflow) Pub/Sub, Cloud Functions, Data Fusion, Data Transfer Py Spark/Spark, Python, SQL (Java/Scala a plus) Cloud Composer (Airflow) orchestration Data warehouse & pipeline design + performance tuning Cloud IAM — data security & access governance Good to Have
Legacy migration (Hadoop/Teradata/on-prem ETL) GCP Kubernetes Engine (GKE), Cloud Storage CI/CD, Git, infrastructure-as-code (Terraf

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