About this role
EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com.
EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.
Header Description
Role Description This role sits within the Risk & Compliance Product Team, working closely with the Data Discovery team. The Data Discovery team builds datasets/tables, and this role is responsible for validating those outputs before they are consumed by product use cases
Location Gurgaon (3 days in office withno exceptions)
Experience 4-8 Years
Start Date Immediate
Must-Have Skills • Strong SQL expertise (mandatory) • Experience in Banking / Financial Services domain (mandatory) • Strong Communication and stakeholder management skills • Experience in either: • Data Validation / Data Testing, OR • Data Engineering / ETL / Data Build
• Strong understanding of: • Data structures and tables • Data sanity checks and validation techniques
Key Responsibilities • Validate datasets and tables generated by upstream data teams, including legacy and POA data systems, to ensure accuracy and reliability • Execute SQL-based validation to verify data accuracy and completeness • Cross-check source vs output data (table-level validation, not complex mapping ownership) • Identify data issues, anomalies, and inconsistencies and drive resolution • Collaborate with data teams to confirm expected outputs and business logic
• Validate datasets and tables generated by upstream data teams, including legacy and POA data systems, to ensure accuracy and reliability • Execute SQL-based validation to verify data accuracy and completeness • Cross-check source vs output data (table-level validation, not complex mapping ownership) • Identify data issues, anomalies, and inconsistencies and drive resolution • Collaborate with data teams to confirm expected outputs and business logic
Graduate in Computer Science, Data Science, or related field. years of experience in data engineering or related field.