GCP Data Engineer
Zensar Technologies (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 8–18 LPA
Posted on 31 Aug
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and maintain scalable ETL/ELT data pipelines primarily using PySpark and Python on Google Cloud Platform.
- Build and manage data ingestion and processing solutions across various GCP services including BigQuery, Dataproc, Dataflow, Pub/Sub, Cloud Storage, and Composer (Airflow).
- Optimize data workflows for performance, scalability, and cost efficiency while ensuring data quality, governance, and compliance standards.
Minimum Requirements
- Strong programming experience in Python and PySpark for large-scale data processing.
- Solid experience with Google Cloud Platform services: BigQuery, Dataproc, Dataflow, Cloud Storage, Pub/Sub, Cloud Composer (Airflow).
- Proficient in SQL and relational databases with experience building batch and real-time data pipelines.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in optimizing Spark jobs and distributed computing architectures for cost and performance efficiencies.
- Familiarity with cloud-native data engineering practices and working collaboratively with Data Scientists, Analysts, and Application teams.
- Exposure to DevOps practices including Git, CI/CD pipelines, and Agile methodologies.