Senior Data Engineer

About EXL

EXL is a worldwide analytics and digital services organization that helps clients improve performance and create new growth opportunities. By combining industry knowledge with data, analytics, cloud, and AI capabilities, the company builds adaptable, scalable solutions and delivers complex operations for major businesses across insurance, healthcare, banking and financial services, media, retail, and other sectors. EXL was established on values of innovation, collaboration, excellence, integrity, and respect. Headquartered in New York, it has a workforce of more than 34,000 people and operates through 50+ offices across six continents.

Role Overview

This position is for a Senior Data Engineer / Databricks Data Engineer based in Gurgaon or Bangalore. The role focuses on designing, building, and tuning scalable data pipelines and lakehouse solutions on Databricks. It requires strong practical experience in data engineering and distributed data processing.

Responsibilities

• Build, maintain, and improve ETL and ELT pipelines on Databricks using PySpark, Spark SQL, and Delta Lake.
• Create and refine ingestion frameworks, data transformations, and complete batch and streaming workflows.
• Implement Delta Lake solutions with features such as version control, schema evolution, and ACID-compliant processing.
• Partner with stakeholders to understand data needs and convert them into scalable engineering solutions.
• Administer Databricks clusters, jobs, and notebooks with an eye on speed and cost.
• Connect Databricks workflows with cloud and streaming tools such as Azure Data Lake, AWS S3, Event Hub, Kafka, Synapse, and Redshift.
• Strengthen data reliability through validation checks, monitoring, and observability practices.
• Support data modeling, metadata handling, and platform best practices.
• Work alongside data scientists, analysts, and business teams to enable analytics and machine learning use cases.

Requirements

• At least 8 years of data engineering experience, with deep hands-on exposure to Databricks.
• Strong working knowledge of Spark, including PySpark and Spark SQL, for distributed data processing.
• Advanced SQL skills and experience handling large datasets.
• Clear understanding of Delta Lake, medallion architecture, and scalable lakehouse design patterns.
• Working familiarity with CI/CD, Git, and modern DevOps practices for data pipelines.
• Exposure to structured and unstructured data, data quality frameworks, and performance tuning techniques.

Work Mode

This is a complete work-from-office role with a 5-day office schedule.

Location

Gurgaon and Bangalore, India.

Eligibility

Any graduate can apply.

Compensation

The offered salary range is INR 14,00,000 to INR 24,00,000 per year.