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Data Analyst
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Salary
≈ $16k – $31k per year (Estimated)
Location
In office (Pune)
Seniority
Senior · 5+ years exp
Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on Jul 22, 2026. EXL scores B on the Alion truth index.
Overview
Company
Impact
Profile match
EXL, legally ExlService Holdings, is a data analytics, AI and digital operations company headquartered in New York that runs outsourced business processes and builds data and AI solutions for insurers, healthcare organisations, banks, media and retail companies. Founded in 1999 and listed on Nasdaq, it has more than 60,000 employees across six continents, with large delivery centers in Noida, Gurgaon, Pune, Bengaluru and Chennai and a newer AI hub in Dublin. It hires data scientists and data engineers, GenAI and MLOps engineers, analytics managers, solution consultants and client partners, plus talent acquisition, finance and medical coding staff.
Must-Have:
- 4+ / 5+ yearsof professional experience as a Data Analyst with good decision-making, analytical and problem-solving skills.
- SQL, Pyspark, Python with Banking Domain knowledge - Credit & Lending.
Working knowledge / experience of Big Data frameworks like Hadoop, Hive and Spark.
- Hands-on experience in query languages like HQL or SQL (Spark SQL) for Data exploration.
- Data mapping: Determine the data mapping required to join multiple data sets together across multiple sources.
- Documentation - Data Mapping, Subsystem Design, Technical Design, Business Requirements.
- Exposure to Logical to Physical Mapping, Data Processing Flow to measure the consistency, etc.
- Data Asset design / build: Working with the data model / asset generation team to identify critical data elements and determine the mapping for reusable data assets.
- Understanding of ER Diagram and Data Modelling concepts
- Exposure to Data quality validation
- Exposure to Data Management, Data Cleaning and Data Preparation
- Exposure to Data Schema analysis.
- Exposure to working in Agile framework.
- Knowledge of Credit Risk Frameworks such as Basel II, III, IFRS 9 and Stress Testing and understanding their drivers - advantageous
Must-Have:
- 4-6 yearsof professional experience as a Data Analyst with good decision-making, analytical and problem-solving skills.
- SQL, Pyspark, Python with Banking Domain knowledge - Credit & Lending.
Working knowledge / experience of Big Data frameworks like Hadoop, Hive and Spark.
- Hands-on experience in query languages like HQL or SQL (Spark SQL) for Data exploration.
- Data mapping: Determine the data mapping required to join multiple data sets together across multiple sources.
- Documentation - Data Mapping, Subsystem Design, Technical Design, Business Requirements.
- Exposure to Logical to Physical Mapping, Data Processing Flow to measure the consistency, etc.
- Data Asset design / build: Working with the data model / asset generation team to identify critical data elements and determine the mapping for reusable data assets.
- Understanding of ER Diagram and Data Modelling concepts
- Exposure to Data quality validation
- Exposure to Data Management, Data Cleaning and Data Preparation
- Exposure to Data Schema analysis.
- Exposure to working in Agile framework.
- Knowledge of Credit Risk Frameworks such as Basel II, III, IFRS 9 and Stress Testing and understanding their drivers - advantageous
Graduate in Computer Science, Data Science, or related field. 2-3 years of experience in data engineering or related field.
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