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.

Work arrangement
No