Senior GCP Data Engineer: Big Data Pipelines & Analytics

Tata Consultancy Services Limited; Phoenix (AZ); On-site; USD 100,000 - 120,000; Full time

Benefits offered by this job

Medical Coverage

Dental & Vision

401K Plan

Time Off & Holidays

Certification & Training

Job summary

Tata Consultancy Services Limited in Phoenix, AZ invites a skilled GCP Data Engineer to join our technology team. You will design and optimize data pipelines using GCP, Spark, Python and SQL to deliver scalable analytics.

The role requires 6+ years of hands-on experience with Big Data and data warehousing, CI/CD, and cloud best practices, with a focus on developing reliable data solutions for enterprise workloads.

Qualifications

• 6+ years of hands-on software development experience with Big Data & Analytics solutions.
• Strong experience designing, developing, and optimizing data pipelines for large-scale data processing using Big Data and GCP technologies.
• Proficiency in SQL and database systems, with experience in designing data models for performance and scalability.
• Experience with CI/CD pipelines, automated testing frameworks, and source code management tools (Git, Jenkins).

Responsibilities

• Design, develop, and optimize data pipelines for large-scale data processing on GCP and Big Data technologies.
• Build and optimize data models and storage strategies for performance and scalability.
• Collaborate with product teams to implement end-to-end analytics solutions.
• Ensure CI/CD integration and robust testing across data engineering workstreams.

Skills

Python

PySpark

GCP

ETL

Big Data

Data Analytics

SQL

Git

Tools

Airflow

DataProc

PubSub

Hadoop Hive

Spark

Shell scripting

GitHub

GitLab

Bitbucket

SVN

Job description

Tata Consultancy Services Limited in Phoenix, AZ invites a skilled GCP Data Engineer to join our technology team. You will design and optimize data pipelines using GCP, Spark, Python and SQL to deliver scalable analytics.

The role requires 6+ years of hands-on experience with Big Data and data warehousing, CI/CD, and cloud best practices, with a focus on developing reliable data solutions for enterprise workloads.