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-effective 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.
Solid 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.

Valuable to Have
Experience with data modelling, Terraform, dbt, and data warehousing concepts.

Education:

Any Graduation or Any Post Graduation.

📌 Gcp Data Engineering Consultant Bengaluru
🏢 MyCareernet
📍 Bengaluru