- Design, develop, and optimize data pipelines using Databricks, Apache Spark, and Delta Lake.
- Implement data ingestion, transformation, and integration workflows for large-scale datasets.
- Ensure data quality, reliability, and performance across all pipelines.
- Collaborate with data architects and analysts to enable analytics and reporting capabilities.
- Apply best practices for Lakehouse architecture and cloud-based data engineering.
- Monitor and troubleshoot pipeline performance, ensuring scalability and efficiency.
- Work within an Agile framework for sprint planning, backlog management, and continuous delivery.
- Design, develop, and optimize data pipelines using Databricks, Apache Spark, and Delta Lake.
- Implement data ingestion, transformation, and integration workflows for large-scale datasets.
- Ensure data quality, reliability, and performance across all pipelines.
- Collaborate with data architects and analysts to enable analytics and reporting capabilities.
- Apply best practices for Lakehouse architecture and cloud-based data engineering.
- Monitor and troubleshoot pipeline performance, ensuring scalability and efficiency.
- Work within an Agile framework for sprint planning, backlog management, and continuous delivery.
- 5+ years of experience in data engineering with strong focus on Databricks.
- Hands-on expertise in Apache Spark, Delta Lake, and Databricks Lakehouse architecture.
- Strong knowledge of Python, PySpark, and SQL.
- Experience with cloud platforms (Azure preferred) and data integration tools.
- Strong SQL skills (joins, window functions, optimization)
- Experience with cloud platforms (Azure / AWS / GCP)
- Knowledge of ETL/ELT, CDC, SCD (Type 1 & 2)
- Familiarity with CI/CD pipelines and DevOps practices.
- Understanding of data governance, metadata management, and performance tuning.
- Excellent problem-solving and communication skills.
Skills Required
- 5+ years of experience in data engineering
- Hands-on expertise with Databricks
- Experience with Apache Spark and Delta Lake
- Strong knowledge of Python and PySpark
- Strong SQL skills (joins, window functions, optimization)
- Experience with cloud platforms and data integration tools
- Azure experience (preferred)
- Knowledge of ETL/ELT, CDC, SCD (Type 1 & 2)
- Familiarity with CI/CD pipelines and DevOps practices
- Understanding of data governance, metadata management, and performance tuning
- Excellent problem-solving and communication skills
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.
