Azure Databricks, ADF, Pyspark, Python, Terraform

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: Strong 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