DATABRICKS Data Engineer

Tata Consultancy Services • IT Consulting & Digital Transformation • IT Outsourcing & Dedicated Teams • Bachelor's Degree • Python • SQL • ETL/ELT • 2 days ago

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Salary

≈ $14k – $35k per year (Estimated)

Location

In office (Visakhapatnam)

Seniority

Middle · 4+ years exp

Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Oct 21, 2026.

Overview

Company

Impact

Profile match

Tata Consultancy Services

Tata Consultancy Services (TCS) is a global leader in IT services, consulting, and digital business solutions operating as the flagship tech subsidiary of the Tata Group. Headquartered in Mumbai, India, the company delivers end-to-end capabilities spanning cloud computing, enterprise platforms, cybersecurity, and artificial intelligence to major global enterprises. Employing over 500,000 professionals across dozens of countries, it stands as one of the world's largest IT outsourcing and technology transformation partners.

tcs.com • HQ: Mumbai, India • Management Consulting • Systems Integrators • IT Consulting & Digital Transformation • IT Outsourcing & Dedicated Teams • Est. 1968

Tech stack of Tata Consultancy Services

Role: Engineer. Skills: Azure, Data Migration, SQL, Data Integration. Experience: 4 - 8 Years. Qualification: Bachelor Of Engineering

Hands-on experience with Databricks platform, including:
PySpark / Spark SQL for data processing and transformation
Delta Lake for ACID-compliant data storage
Notebooks for workflow orchestration and collaborative development
Strong programming skills in Python and SQL.
Experience in data ingestion from batch and streaming sources.
Knowledge of ETL/ELT design patterns and data pipeline optimization.
Familiarity with cloud data storage and compute environments (AWS, Azure, or GCP).
Basic understanding of workflow orchestration tools (Airflow, Databricks Jobs).
Exposure to DevOps concepts, CI/CD pipelines, and version control (Git).
Awareness of data security, access control, and compliance considerations.
Understanding of performance tuning, partitioning, and caching strategies in Spark.

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Informatica

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