Job Summary:
We are looking for a Data Warehouse Developer with strong expertise in SQL and a deep understanding of Data Warehouse (DWH) concepts. The role involves designing, developing, and optimizing SQL queries for data extraction, transformation, and reporting within large-scale data warehouse environments. The ideal candidate will translate business needs into efficient SQL queries and data models to support analytics and decision-making.
Key Responsibilities:
- Develop complex SQL queries for data extraction, transformation, and loading (ETL) processes within the data warehouse—Document SQL development standards and procedures.
- Design and optimize SQL scripts to improve data retrieval performance and data quality.
- Implement and maintain dimensional data models (star schema, snowflake schema) using SQL.
- Write stored procedures, functions, views, and triggers to automate data workflows.
- Collaborate with BI teams and business stakeholders to gather reporting requirements and translate them into SQL-based solutions. Optimize existing SQL queries and database objects for better performance. Work with large datasets to validate and ensure data accuracy and consistency.
- Perform data profiling and data cleansing using SQL to ensure high-quality data in the warehouse.
- Troubleshoot and debug SQL code related to data warehousing processes.
- Manage Slowly Changing Dimensions (SCD) to accurately track historical data changes over time.
- Ensure data quality and consistency by implementing validation rules and data cleansing procedures within the data warehouse. Develop and maintain metadata and documentation for data warehouse architecture, schemas, and ETL processes.
Must Have Skills:
- Strong SQL skills: complex queries, joins, stored procedures, views, and performance tuning.
- Solid understanding of Data Warehouse concepts: fact/dimension tables, slowly changing dimensions (SCD), schema design.
- Experience with AWS data services, including but not limited to:
- Amazon Redshift (managed data warehouse)
- AWS Glue (ETL service)
- Amazon S3 (data lake/storage)
- AWS Lambda (serverless compute for ETL automation)
- Amazon RDS/Aurora (relational databases)
- Familiarity with cloud architecture and security best practices on AWS.
- Experience with ETL development and orchestration in AWS environments.
- Ability to optimize data workflows and SQL queries for performance and cost-efficiency on AWS
Good to Have Skills:
- Design and develop dimensional and normalized data models (star schema, snowflake schema) to efficiently support analytical queries.
- Understand the differences between OLTP and OLAP systems and design solutions tailored for analytical workloads. Collaborate with business analysts and data consumers to gather requirements and translate them into data warehouse design and reporting solutions.
- Apply data governance and security best practices to protect sensitive data within the warehouse.
- Use SQL extensively for data extraction, transformation, and analysis in the data warehouse
Key Skills - AWS Solutions Architecture, Omnia Platform Knowledge, Vector Db, RDBMS with ANSI SQL
ResponsibilitiesAssist in data collection and processing, Support data pipeline development, Document data engineering processes, Perform basic data analysis, Collaborate with senior data engineers.
QualificationsBachelor's/Master's in Engineering 3-5 years
Skills Required
- Strong SQL skills including complex queries, joins, stored procedures, views, and performance tuning
- Solid understanding of Data Warehouse concepts: fact/dimension tables, slowly changing dimensions, schema design
- Experience with AWS data services: Amazon Redshift, AWS Glue, Amazon S3, AWS Lambda, Amazon RDS/Aurora
- Familiarity with cloud architecture and security best practices on AWS
- Experience with ETL development and orchestration in AWS environments
- Ability to optimize data workflows and SQL queries for performance and cost-efficiency on AWS
- Bachelor's or Master's degree in Engineering
- 3-5 years relevant experience in data engineering / data warehousing
- Design and develop dimensional and normalized data models (star/snowflake schemas)
- Understand differences between OLTP and OLAP systems and design analytical solutions
- Apply data governance and security best practices to protect sensitive data
- Experience or knowledge of AWS Solutions Architecture, Omnia Platform, Vector DB, RDBMS (ANSI SQL)
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.
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