JOB DESCRIPTION

Key Responsibilities:
Design and develop scalable data pipelines using Azure Data Factory (ADF) and Azure Databricks.
Build and optimize large-scale ETL/ELT processes using PySpark and Python.
Ingest data from various structured and unstructured sources into Azure Data Lake.
Develop batch and real-time data processing solutions.
Create reusable data transformation frameworks and data quality checks.
Implement Infrastructure as Code (IaC) using Terraform.
Manage Azure resources including Data Lake Storage, Key Vault, Databricks, ADF, and Monitoring services.
Optimize Spark jobs for performance, scalability, and cost efficiency.
Develop CI/CD pipelines for deployment automation.
Collaborate with business stakeholders, architects, and development teams to define data requirements and solutions.
Support production deployments and troubleshoot data pipeline issues.
Follow data governance, security, and compliance standards.

Required Technical Skills:

1) Azure Services: Azure Databricks,



Azure Data Factory (ADF), Azure Data Lake Storage Gen2, Azure Key Vault, Azure Monitor, Azure DevOps

2) Data Engineering: Robust expertise in ETL/ELT development, Data Warehousing concepts, Data Modeling (Star Schema, Snowflake Schema). Batch and Streaming Data Processing

3) Programming: Python, PySpark, SQL

4) Infrastructure as Code: Terraform, Azure Resource Management Concepts

5) Databases: Azure SQL Database, SQL Server, PostgreSQL, Cosmos DB (Preferred)

6)DevOps: Azure DevOps, Git, CI/CD Pipeline Implementation

Mandatory Skills:
Azure Databricks
Azure Data Factory (ADF)
PySpark
Python
Terraform
SQL
Azure Data Lake Storage (ADLS)
Azure DevOps

Preferred Skills:
Delta Lake
Unity Catalog
Spark Optimization
Data Governance
Real-time Streaming (Kafka/Event Hub)
Synapse Analytics
Machine Learning Integration

📌 Azure Databricks, Adf, Pyspark, Python, Terraform Chennai
🏢 Tata Consultancy Services
📍 Chennai