Technology & Transformation - Engineering - Manager - Azure Databricks - Bangalore

Technology & Transformation - Engineering - Azure Databricks - Bangalore

• Job requisition ID : 106097
• Location: Bengaluru
• Entity: Deloitte Touche Tohmatsu India LLP

The Team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.

We are seeking highly skilled Databricks Data Engineers to join our data modernization team. You will play a pivotal role in designing, developing, and maintaining robust data solutions on the Databricks platform. Your experience in data engineering, along with a deep understanding of Databricks, will be instrumental in building solutions to drive data-driven decision-making across a variety of customers.

Work Profile

Azure Databricks/dbt Data Engineer in the analytics domain designs, builds, and maintains high-performance ETL/ELT pipelines using Databricks (PySpark/SQL) and dbt to transform raw data into curated, analytics-ready models. This role requires 5-10 years' experience in Azure cloud ecosystems, strong dimensional modelling skills, and expertise in implementing data pipeline, data quality, and governance using modern data stack tools.

Key Responsibilities

• Data Modelling & Transformation: Architect and develop advanced data transformation workflows using dbt (models, tests, macros) within the Databricks Medallion Architecture (Bronze/Silver/Gold).

• Pipeline Development: Build and optimize scalable, high-throughput, and low-latency data pipelines using Azure Databricks (PySpark,SQL), dbt, Airflow, and Azure Data Lake Storage (ADLS).