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Mid-senior GCP data engineer in Bangalore with common stack and broad requirements increases applicant density.
GCP data engineering skills are broadly transferable across industries.
Explicit 6+ years requirement and mandatory GCP/BigQuery/PySpark skills create strict shortlisting filters.
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Design, develop, and optimize scalable ETL/ELT data pipelines using GCP services like BigQuery, Dataflow, Dataproc, Cloud Storage, and Pub/Sub.
Develop data processing applications with Python, PySpark, and SQL to handle ingestion, transformation, cleansing, and validation.
Implement and maintain batch and real-time data processing pipelines with focus on performance, cost efficiency, and data governance.
Minimum 6 years of experience in data engineering or related roles.
Strong hands-on expertise in Google Cloud Platform data engineering tools: BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub.
Proficient in Python, PySpark, and SQL for data processing applications.
Work Experience Required: 6+ years
Experienced in designing efficient data models and warehouse solutions in BigQuery for large-scale environments.
Skilled at optimizing data pipelines and queries for scalability and cost efficiency on GCP.
Comfortable collaborating closely with cross-functional teams including Data Scientists, Architects, Analysts, and business stakeholders.