Required Skills & Experience
- 5–7 years of experience in data engineering, with at least 2–3 years of Databricks hands-on experience.
- Strong expertise in Apache Spark (PySpark/Scala/SQL) and distributed data processing.
- Solid experience with Delta Lake, Lakehouse architecture, and data modeling.
- Hands-on experience with at least one cloud platform: Azure Data Lake, AWS S3, or GCP BigQuery/Storage.
- Strong proficiency in SQL for data manipulation and performance tuning.
- Experience with ETL frameworks, workflow orchestration tools (Airflow, ADF, DBX Workflows).
- Good understanding of CI/CD, Git-based workflows, and DevOps practices.
- Exposure to MLOps and MLflow is a strong plus.
- Knowledge of data governance, cataloging, and security frameworks.
Responsibilities
Required Skills & Experience
- 5–7 years of experience in data engineering, with at least 2–3 years of Databricks hands-on experience.
- Strong expertise in Apache Spark (PySpark/Scala/SQL) and distributed data processing.
- Solid experience with Delta Lake, Lakehouse architecture, and data modeling.
- Hands-on experience with at least one cloud platform: Azure Data Lake, AWS S3, or GCP BigQuery/Storage.
- Strong proficiency in SQL for data manipulation and performance tuning.
- Experience with ETL frameworks, workflow orchestration tools (Airflow, ADF, DBX Workflows).
- Good understanding of CI/CD, Git-based workflows, and DevOps practices.
- Exposure to MLOps and MLflow is a strong plus.
Bachelor's/Master's in Engineering 0-2 years
Skills Required
- 5-7 years of experience in data engineering
- 2-3 years hands-on Databricks experience
- Strong expertise in Apache Spark (PySpark/Scala/SQL)
- Experience with Delta Lake, Lakehouse architecture, and data modeling
- Hands-on experience with at least one cloud platform: Azure Data Lake, AWS S3, or GCP BigQuery/Storage
- Strong proficiency in SQL for data manipulation and performance tuning
- Experience with ETL frameworks and workflow orchestration tools (Airflow, ADF, DBX Workflows)
- Understanding of CI/CD, Git-based workflows, and DevOps practices
- Exposure to MLOps and MLflow
- Knowledge of data governance, cataloging, and security frameworks
- Bachelor's/Master's in Engineering
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.







