EXL is a global analytics and digital solutions company that partners with clients to improve business outcomes and unlock growth. Bringing together deep domain expertise with robust data, powerful analytics, cloud, and AI, we create agile, scalable solutions and execute complex operations for the worlds leading corporations in industries including insurance, healthcare, banking and financial services, media, and retail, among others. Focused on driving faster decision-making and transforming operating models, EXL was founded on the core values of innovation, collaboration, excellence, integrity and respect. Headquartered in New York, our team is over 34,000 strong, with more than 50 offices spanning six continents.

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 EXLs Human Resources team, as well as our hiring managers.

Role Overview:

EXL is seeking a Data Analyst with strong big data and analytics expertise to work on large-scale datasets within the US Banking domain. This role involves deep data extraction, transformation, and analysis using SQL, Python, and PySpark while working directly with clients to deliver high-impact insights.

This is an ideal role for professionals experienced in data wrangling on enterprise-scale data platforms who enjoy solving complex business problems in financial services.

Key Responsibilities:

- Extract, transform, and analyze large volumes of structured and semi-structured data

- Write advanced SQL queries for complex joins, aggregations, subqueries, and performance optimization

- Use Python for data manipulation, analysis, and automation

Work with PySpark to:

- Establish Spark sessions

- Process large datasets

- Perform distributed data transformations

- Pull and integrate data from Hadoop ecosystems (Hive/Impala) and Oracle databases

- Perform complex data wrangling, cleansing, and merging across multiple sources

- Translate raw data into actionable business insights

- Work directly with clients to understand data requirements and present findings

- Ensure data accuracy, validation, and quality checks

- Support ad-hoc analytical requests and reporting needs

Required Skills & Experience:

- 5-7 years of experience in Data Analytics / Data Engineering support / BI Analytics

- Advanced proficiency in SQL

- Intermediate proficiency in Python for analytics

- Hands-on experience with PySpark and distributed data processing

- Experience working with Hadoop platforms (Hive, Impala)

- Strong experience handling large datasets and complex data transformations

- Knowledge of Oracle databases

- Experience in US Banking / Financial Services domain

- Strong problem-solving and analytical thinking

- Excellent communication skills for client-facing interactions

Nice to Have:

- Experience in data pipeline optimization

- Exposure to big data performance tuning

- Understanding of data governance and quality frameworks

- Experience with reporting/BI tools