Data Engineer, Data Analyst

EXL; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

EXL is seeking a data engineer toDesign, build, and operate scalable ETL/ELT data pipelines that ingest, transform, and load data from multiple sources in Pune. The role emphasizes Spark/PySpark and extensive SQL work for large-scale data processing.

You will engineer and maintain data platforms, ensure data quality, governance, and security, and support CI/CD and DevOps practices for data operations with strong core software engineering foundations.

Qualifications

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

Responsibilities

• Design, build, and operate scalable ETL/ELT data pipelines ingesting data from multiple sources.
• Engineer and maintain data platforms (data lakes and data warehouses) with reliability and resilience.
• Implement system integrations using APIs, streaming, and data integration tools for end-to-end data flows.
• Apply Spark/PySpark and SQL for large-scale processing and data transformations.
• Embed data quality, governance, security, and regulatory controls across pipelines.
• Enable DevOps for data with CI/CD, orchestration, monitoring, and production support.
• Hands-on expertise in Prophecy pipeline development and deployment and PySpark pipeline engineering.

Skills

ETL/ELT pipelines

Spark / PySpark

SQL

APIs

CI/CD

Data governance

Data pipelines

DevOps for data

Education

Bachelor's degree in Computer Science or Data Science

Tools

Prophecy

Job description

• Experience (In Years) 3-6
• Job Location Pune

Job Description

• Design, build, and operate scalable Extract, Transform, Load / Extract, Load, Transform (ETL/ELT) data pipelines (batch and real-time) to ingest, transform, and load data from multiple sources.
• Engineer and maintain data platforms (data lakes and data warehouses) with strong reliability, availability, and operational resilience.
• Implement system integrations using Application Programming Interfaces (APIs), streaming, and enterprise data integration tools to ensure consistent end-to-end data flows.
• Apply Apache Spark / Python for Spark (Spark/PySpark) and advanced Structured Query Language (SQL) for large-scale processing, optimization, and perform data transformations.
• Embed data quality, governance, security, and regulatory controls across pipelines and datasets.
• Enable development and operations (DevOps) for data through Continuous Integration / Continuous Delivery (CI/CD), orchestration and scheduling, monitoring, troubleshooting, and production support.
• Hands-on expertise in Prophecy pipeline development and deployment, PySpark analysis, and PySpark pipeline engineering (build and release), alongside strong core software engineering fundamentals

Responsibilities

Qualifications

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