About the role

15900: Lead Data Engineer (Databricks)

📍 Location: Gurugram & Bangalore
🏢 Work Mode: Work From Office (5 Days)
💼 Experience: 9+ Years

Key Skills:

Role Overview

We are looking for a highly skilled Senior Data Engineer with strong expertise in Databricks, PySpark, and SQL to design, build, and optimize scalable data pipelines and modern lakehouse solutions. The ideal candidate will have extensive experience in distributed data processing, data engineering best practices, and cloud-based data platforms, enabling organizations to unlock insights from large-scale data.

This role requires close collaboration with data scientists, analysts, and business stakeholders to deliver high-performance data solutions that support analytics and machine learning initiatives.

Key Responsibilities

Design, build, and maintain ETL/ELT pipelines on Databricks using PySpark, Spark SQL, and Delta Lake.
Develop and optimize data ingestion frameworks, data transformations, and end-to-end workflows for batch and streaming use cases.
Implement Delta Lake-based architectures, including versioning, schema evolution and ACID-compliant pipelines.
Work with stakeholders to understand data requirements and translate them into scalable data engineering solutions.
Manage and optimize Databricks clusters, jobs, and notebooks for performance and cost efficiency.
Ensure data quality, reliability, and observability through validation frameworks and monitoring.
Contribute to data modeling, metadata management, and best practices within the data platform.

Must have Skills & Experience

• 5+ years of experience in data engineering with 3+ years of hands on expertise in

Databricks.

• 7+ years of experience in Data Engineering development

• Must have good understanding of DWH concepts and ETL process/standards

• Should be able to lead 2-3 member team

• Hands-on experience with Spark (PySpark/Spark SQL) and distributed data

processing.

• Solid SQL knowledge and experience working with large-scale datasets

• Strong understanding of Delta Lake, medallion architecture, and scalable lakehouse

patterns.

• Good understanding of CI/CD, Git, and modern DevOps practices for data pipelines.

• Familiarity with structured/unstructured data, data quality frameworks, and

performance tuning.

Education

Bachelor’s Degree in Computer Science, Software Engineering, MIS, or an equivalent combination of education and experience.