Role Overview

We are looking for a Lead Data Engineer with strong experience in Azure Data Engineering, Python/PySpark, SQL, and Data Warehousing. The role involves designing scalable data pipelines, leading Azure ETL solutions, and providing technical guidance to the team.

Key Responsibilities

Design and develop scalable data pipelines using Python/PySpark.
Architect and implement Azure ETL/ELT solutions using Databricks, Data Factory, Blob Storage, Synapse, Azure SQL, and Lakebase.
Work with cross-functional teams to translate business requirements into technical solutions.
Lead code reviews, ensure engineering best practices, and maintain technical documentation.
Mentor junior engineers and provide technical leadership.
Troubleshoot data, pipeline, and performance issues.
Use Git, Azure DevOps, and Jira for source control and project delivery.

Required Skills





8+ years of experience in Data Engineering/Data Warehousing.
5+ years of experience with Python/PySpark.
8+ years of experience with SQL, including complex queries, stored procedures, and functions.
Strong experience with Azure Databricks, Data Factory, Blob Storage, Synapse, Azure SQL, Lakebase, and Unity Catalog.
Knowledge of Azure Functions, Logic Apps, Azure VMs, Git, and Azure DevOps.
Solid problem-solving, communication, and leadership skills.

Preferred

Azure Data Engineer certification is a plus.
Experience with Lakehouse architecture and data governance.

Role Details

Role: Lead Data Engineer

Employment: Full-Time, Permanent

Experience: 8+ Years

Education: B.Tech/B.E., BCA, B.Sc., or any relevant postgraduate qualification

📌 Lead Data Engineer (Bengaluru)
🏢 Inxiteout
📍 Bengaluru