GCP Bigquery

Good to have skills: Cloud Composer, Dataflow, Pub/Sub, Looker, Terraform

Key Responsibilities:

• Design, develop, and maintain BigQuery datasets, tables, views, and SQL transformations aligned to analytics and reporting needs.
• Build and support ETL/ELT pipelines leveraging GCS for ingestion and Dataproc for distributed processing where required.
• Optimize BigQuery performance and cost through partitioning, clustering, query tuning, and efficient data modeling practices.
• Implement data quality checks, validation routines, and reconciliation processes to ensure trustworthy outputs.
• Collaborate with cross-functional teams to gather requirements, define data contracts, and deliver curated datasets.
• Monitor pipeline health, troubleshoot failures, perform root-cause analysis, and drive timely resolution.
• Maintain clear technical documentation for pipelines, datasets, transformations, and operational runbooks.
• Follow secure data handling practices and support access controls and governance standards within GCP. Minimum Qualifications:
• Education: BTECH, MTECH, MCA, MSC.
• 3–5 years of experience in data engineering or analytics engineering roles with hands-on BigQuery usage.
• Strong SQL skills with experience building transformations, aggregations, and analytical datasets in BigQuery.
• Experience working with ETL/ELT concepts, batch processing, and data pipeline troubleshooting.
• Working knowledge of GCS for data storage, ingestion patterns, and lifecycle handling.
• Exposure to Dataproc for Spark/Hadoop-based processing and job execution in GCP environments. Preferred Qualifications:
• Experience designing dimensional or curated data models (e.g., star/snowflake) for analytics consumption in BigQuery.
• Familiarity with orchestration and scheduling approaches for ETL workflows and dependency management.
• Proven ability to improve pipeline reliability and performance through monitoring, alerting, and operational best practices.
• Experience with data governance practices including dataset organization, access management, and documentation standards.
• Strong stakeholder collaboration skills to translate business requirements into scalable, maintainable data solutions.