Walk-in | Azure Data Engineer

Tata Consultancy Services Limited; Hyderabad; On-site; INR 1,000,000 - 1,800,000; Full time

Job summary

Tata Consultancy Services Limited is seeking an Azure Data Engineer to join our Hyderabad data engineering team. The role focuses on building and optimizing large-scale data processing pipelines using Databricks, Synapse, Snowflake and AWS integrations.

Ideal candidates will have strong Python/PySpark skills, CI/CD discipline, and experience automating data workflows. You will collaborate with Data Product Owners to design robust pipelines and scalable architectures.

Qualifications

• Must have hands-on experience with Databricks, Snowflake, AWS and Synapse.
• Strong Python/Scala and PySpark skills for data processing.
• Knowledge of CI/CD pipelines and infrastructure as code.
• Experience in automating data workflows and data integration.
• Ability to define data processing pipelines and schedules with Data Product Owners.

Responsibilities

• Collaborate with data product owners to define pipelines and schedules.
• Enable and onboard new tools and services.
• Configure tools and services for optimal performance.
• Establish integration patterns for various tools and services.
• Manage and deploy linked services, datasets, and pipelines.

Skills

Big Data Processing

Python

PySpark

Scala

SQL

CI/CD

Automation

Tools

Databricks

Snowflake

AWS

Azure Synapse

SQL

Python

Pyspark

Job description

Greetings from TCS!!!

Position: Azure Data Engineer

Job Location: Hyderabad

Experience: 5-10 years

Notice Period: 90 days or above 90 days

Interview mode: WALK-IN-DRIVE

Walk-in-Details:

Date: Saturday 24th Oct 2026

Time: 9:00 AM 1:00 PM

BranchFull Address of Drive location

Deccan Park -Hyderabad

JD :

Detailed Job requirements:

Must Have

• ADB, ADF, Synapse, SQL, Python / PySpark
• Databricks Expertise, Big Data Processing, Python/Scala, Pyspark, Workflow Orchestration, AWS Cloud Integration, Databricks , Snowflake, AWS
• Focuses on automation, CI/CD pipelines, and infrastructure as code.
• Managing and deploying linked services, datasets, and pipelines.
• Collaborates with Data Product Owners and Data Engineers to define data processing pipelines & schedules.
• Enables and onboards new tools/services.
• Configures Tools/Services for optimum performance.
• Establishes Integration patterns for various tools/services.