Azure + Databricks

Job Title: Azure + Databricks

Experience: 4 to 7 years

Location: Mumbai (only)

Job Summary:

As a Senior Associate, you will take ownership of designing and delivering complex data engineering solutions across cloud and on-premise environments. You'll lead the technical delivery of ETL/ELT frameworks, data lakes, and data warehouses, leveraging Databricks, Azure, and modern data engineering best practices. You will also mentor junior team members and contribute to solution architecture.

Roles & Responsibilities:

• Lead design and development of end-to-end data pipelines using PySpark, SQL, and Azure Databricks.
• Build and optimize data lakes and data warehouse solutions.
• Implement data ingestion, transformation, and orchestration using tools like Azure Data Factory or Apache Airflow.
• Translate business requirements into technical specifications and ensure alignment with data strategy.
• Conduct code reviews, performance tuning, and pipeline optimization.
• Collaborate with cross-functional teams (data science, BI, and architecture) to enable advanced analytics.
• Mentor Associates and support delivery excellence through documentation and process improvements.

Skills Required:

• 47 years of experience in data engineering, with strong proficiency in PySpark, SQL, and Python.
• Expertise in Azure (Data Factory, Databricks, Synapse, ADLS) or other cloud platforms.
• Strong understanding of Data Warehouse, Data Lake, and ETL architecture.
• Proficiency in query optimization, data modelling, and performance tuning.
• Experience working with version control (Git) and CI/CD pipelines.
• Exposure to data governance, security, and metadata management.
• Knowledge of Snowflake, AWS Redshift, or BigQuery is a plus.
• Strong communication and client-interaction skills.
• Cloud certifications (Azure Data Engineer, Databricks) preferred.