EXL

Analyzes business data and runs outsourced operations

Data Analyst

Data AnalysisConfirmed live in the last 24 hours

Full-timePune, Maharashtra, IndiaNo salary listedIn-person

About the Job

Requirements

4+ to 6 years of professional experience as a Data Analyst, with decision-making, analytical, and problem-solving skills.
Experience with SQL, PySpark, and Python, along with banking-domain knowledge in credit and lending.
Working knowledge or experience with big-data frameworks such as Hadoop, Hive, and Spark.
Hands-on experience with HQL or SQL, including Spark SQL, for data exploration.
Ability to determine data mappings needed to join multiple datasets across multiple sources.
Ability to document data mapping, subsystem design, technical design, and business requirements.
Exposure to logical-to-physical mapping and data-processing flows for measuring consistency.
Ability to work with the data model or asset generation team to identify critical data elements and determine mappings for reusable data assets.
Understanding of entity-relationship diagrams and data modeling concepts.
Exposure to data quality validation, data management, data cleaning, data preparation, and data schema analysis.
Exposure to working in an Agile framework.
Graduate in Computer Science, Data Science, or a related field.
2–3 years of experience in data engineering or a related field.

Responsibilities

Determine data mappings to join multiple datasets across multiple sources.
Document data mapping, subsystem design, technical design, and business requirements.
Work with the data model or asset generation team to identify critical data elements and determine mappings for reusable data assets.
Use data-processing flows to measure consistency.

Desired Qualifications

Knowledge of credit-risk frameworks such as Basel II, Basel III, IFRS 9, and stress testing, including understanding their drivers.

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

Graduate in Computer Science, Data Science, or related field. 2-3 years of experience in data engineering or related field.