GCP Senior Data Engineer - S

Tata Consultancy Services; Kolkata District, Chennai District, Bengaluru; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Tata Consultancy Services seeks an experienced Data Engineer to design and optimize scalable data pipelines on Google Cloud Platform. You will implement ETL/ELT workflows, build data models, and ensure governance across data platforms.

You will collaborate with analysts, scientists, and teams to meet data requirements, monitor performance, and automate deployments for reliable data processing and cost efficiency.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 5+ years of experience in Data Engineering and Cloud Data Platforms.
• Hands-on experience with Google Cloud Platform (GCP) services.
• Strong proficiency in SQL and data modeling concepts.
• Experience with BigQuery, Cloud Storage, Dataflow, Pub/Sub, and Dataproc.
• Strong programming skills in Python, Java, or Scala.
• Experience building ETL/ELT pipelines using modern data integration tools.
• Knowledge of distributed data processing frameworks such as Apache Spark.
• Understanding of data warehousing concepts and dimensional modeling.
• Experience with workflow orchestration tools such as Cloud Composer (Airflow).
• Familiarity with version control systems like Git and CI/CD practices.
• Strong problem-solving and analytical skills.

Responsibilities

• Design, build, and optimize scalable data pipelines on GCP.
• Develop and maintain ETL/ELT workflows for ingesting, transforming, and loading data from multiple sources.
• Implement and manage data solutions using GCP services such as BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Composer, and Cloud Functions.
• Create and maintain data models, data marts, and enterprise data warehouses.
• Ensure data quality, governance, security, and compliance across data platforms.
• Collaborate with business stakeholders, data analysts, data scientists, and application teams to understand data requirements.
• Monitor, troubleshoot, and optimize data processing workflows for performance and cost efficiency.
• Implement CI/CD pipelines and infrastructure automation for data engineering deployments.
• Support real-time and batch data processing requirements.
• Document data architecture, workflows, and best practices.

Skills

GCP

SQL

BigQuery

Python

Java/Scala

ETL/ELT pipelines

Data modeling

CI/CD

Git

Apache Spark

Education

Bachelor's degree in CS/IT/Engineering

Tools

BigQuery

Cloud Storage

Dataflow

Dataproc

Pub/Sub

Composer

Cloud Functions

Job description

Key Responsibilities

• Design, build, and optimize scalable data pipelines on GCP.
• Develop and maintain ETL/ELT workflows for ingesting, transforming, and loading data from multiple sources.
• Implement and manage data solutions using GCP services such as BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Composer, and Cloud Functions.
• Create and maintain data models, data marts, and enterprise data warehouses.
• Ensure data quality, governance, security, and compliance across data platforms.
• Collaborate with business stakeholders, data analysts, data scientists, and application teams to understand data requirements.
• Monitor, troubleshoot, and optimize data processing workflows for performance and cost efficiency.
• Implement CI/CD pipelines and infrastructure automation for data engineering deployments.
• Support real-time and batch data processing requirements.
• Document data architecture, workflows, and best practices.

Required Skills & Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 5+ years of experience in Data Engineering and Cloud Data Platforms.
• Hands-on experience with Google Cloud Platform (GCP) services.
• Strong proficiency in SQL and data modeling concepts.
• Experience with BigQuery, Cloud Storage, Dataflow, Pub/Sub, and Dataproc.
• Strong programming skills in Python, Java, or Scala.
• Experience building ETL/ELT pipelines using modern data integration tools.
• Knowledge of distributed data processing frameworks such as Apache Spark.
• Understanding of data warehousing concepts and dimensional modeling.
• Experience with workflow orchestration tools such as Cloud Composer (Airflow).
• Familiarity with version control systems like Git and CI/CD practices.
• Strong problem-solving and analytical skills.