GCP Data Engineer

Tata Consultancy Services; Bengaluru; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Tata Consultancy Services in Bengaluru is seeking a GCP Data Engineer to design and implement scalable data platforms and modern data pipelines on Google Cloud Platform. The role requires hands-on work with BigQuery, PySpark, Cloud Composer (Airflow), Dataflow, Pub/Sub, Python and SQL to support enterprise analytics initiatives.

You will design ETL/ELT pipelines, optimize batch and streaming processing, and collaborate with BI, Analytics, and Data Science teams to deliver analytics-ready

Qualifications

• Hands-on experience with BigQuery, PySpark, Cloud Composer (Airflow), Dataflow, Pub/Sub, Python and SQL to support data engineering and analytics initiatives.

Responsibilities

• Design and develop scalable ETL/ELT pipelines on GCP.
• Build and optimize batch and real-time data processing solutions.
• Develop data ingestion frameworks using BigQuery, GCS, Pub/Sub, and Dataflow.
• Develop data transformation logic using PySpark, Python, and SQL.
• Build and maintain data lakes, data warehouses, and analytics-ready datasets.
• Implement data quality, monitoring, governance, and security frameworks.
• Optimize BigQuery performance, partitioning, clustering, and query execution.
• Collaborate with BI, Analytics, Data Science, and business stakeholders.

Tools

BigQuery

PySpark

Cloud Composer (Airflow)

Dataflow

Pub/Sub

Python

SQL

Job description

Face to Face Interview on 22nd August at Tata Consultancy Services, Yeshwanthpur Industrial Suburb, Yeswanthpur, Bengaluru, Karnataka

Role Summary

We are looking for a GCP Data Engineer with strong expertise in building scalable data platforms and modern data pipelines on Google Cloud Platform (GCP). The ideal candidate should have hands‑on experience with BigQuery, PySpark, Cloud Composer (Airflow), Dataflow, Pub/Sub, Python, and SQL to support enterprise data engineering and analytics initiatives.

Key Responsibilities

• Design and develop scalable ETL/ELT pipelines on GCP.
• Build and optimize batch and real-time data processing solutions.
• Develop data ingestion frameworks using BigQuery, GCS, Pub/Sub, and Dataflow.
• Develop data transformation logic using PySpark, Python, and SQL.
• Build and maintain data lakes, data warehouses, and analytics‑ready datasets.
• Implement data quality, monitoring, governance, and security frameworks.
• Optimize BigQuery performance, partitioning, clustering, and query execution.
• Collaborate with BI, Analytics, Data Science, and business stakeholders.