Looking for a hands‑on Senior Data Engineer – Azure & Databricks with up to 6 years of total experience to build, optimize, and maintain scalable cloud data platforms.
This is an individual contributor role, focused on developing reliable data pipelines and analytics‑ready datasets using Microsoft Azure and Databricks. The role requires strong hands‑on expertise in SQL and Python, along with experience building batch (and basic streaming) data pipelines in a cloud setting.
You will collaborate closely with architects, analytics teams, QA, DevOps, and business stakeholders in a global delivery model.
Must have skillsHands‑on experience delivering Azure‑based data engineering solutions
Cloud & Data Engineering (Azure)

Strong hands‑on experience with Azure data services, including:
Azure Data Lake Storage Gen2 (ADLS)
Azure Data Factory (ADF)
Azure Databricks
Azure Synapse Analytics

Experience designing cloud‑native data lakes and analytical data stores
Solid understanding of batch data pipelines and basic streaming concepts

SQL & Python (Mandatory)
Strong SQL skills (mandatory)




Writing complex queries, joins, aggregations, and transformations
Hands‑on experience working with large datasets in Synapse / Databricks

Strong Python skills (mandatory)
Python for ETL / ELT and data engineering use cases
Hands‑on experience with PySpark in Databricks

Strong understanding of data modeling, transformations, and query performance tuning

Data Processing & Engineering
Hands‑on experience with Spark / PySpark on Databricks
Experience handling structured and semi‑structured data
Understanding of partitioning, schema evolution, and data validation concepts

DevOps & Platform Basics
Working knowledge of Infrastructure as Code (ARM Templates and/or Terraform)
Basic experience with CI/CD pipelines (Azure DevOps or GitHub Actions)
Understanding of logging and monitoring using Azure Monitor / Log Analytics

Collaboration
Ability to work effectively with architects, QA, DevOps, an

📌 Data Engineer (Mumbai)
🏢 dentsu
📍 Mumbai