Key Skills: Pub/Sub, Pyspark, Bigquery, Airflow, Python, GCP, ETL, Terraform, Data Warehousing, SQL, DBT, Data Modelling

Roles and Responsibilities:

- Design, build, and maintain scalable batch and real-time ETL/ELT pipelines using Python, PySpark, Airflow, Pub/Sub, and GCP services.

- Develop and optimize BigQuery data processing solutions, including SQL queries, partitioning, clustering, and cost-efficient execution.

- Build reliable data ingestion and transformation workflows for analytical and operational data sources.

- Implement data validation, quality controls, error handling, lineage, and governance measures across data pipelines.

- Troubleshoot production data pipeline issues, perform root-cause analysis, and improve reliability, throughput, and operational stability.

Skills Required:

- 4 - 7 years of relevant experience in data engineering,



cloud data platforms, or ETL development.

- Strong hands-on experience with Google Cloud Platform data engineering solutions, ETL development, Python, PySpark, and advanced SQL.

- Practical experience developing data solutions with BigQuery, Airflow, Pub/Sub, and related GCP data services.

- Ability to design scalable batch and streaming data architectures for high-volume workloads.

- Experience with data pipeline testing, validation, monitoring, troubleshooting, and production support.

Positive to Have

- Experience with data modelling, Terraform, dbt, and data warehousing concepts.

Education: Any Graduation or Any Post Graduation.

📌 GCP Data Engineering Consultant (Bengaluru)
🏢 Careernet
📍 Bengaluru