← All jobs
E

AWS Data Engineer

EXL

Posted 8 Sept 2026

PuneHigh payGreat Place to Work
Apply on EXL →

Research EXL before you apply

Check ratings, real-employee reviews, verified pay, and interview difficulty.

Glassdoor reviewsRatings, pros/cons, CEO approval↗AmbitionBoxIndia reviews, salaries, interviews↗Levels.fyiVerified compensation by level↗LinkedInPeople, growth, your connections↗

We are seeking a highly skilled AWS Data Engineer with deep expertise in AWS cloud architecture, big data processing, real-time streaming, and modern data lake technologies. The ideal candidate will have strong hands-on experience in Spark (PySpark), Iceberg, EMR, Starburst/Trino, and event-driven architectures, along with experience building real-time and API-driven data applications who can design and build generic solutions for one of our Fortune 500 Client programs in the realm of Financial Master & Reference Data Management. This is high visibility, fast-paced key initiative will integrate data across internal and external sources, provide analytical insights, and integrate with the customer’s critical systems. 

Responsibilities

  • Key Responsibilities 

    • Design and implement scalable, secure, and cost-optimized AWS data architectures.
    • Develop and maintain ETL pipelines using AWS Lambda and AWS Glue ETL.
    • Configure and manage AWS Glue Crawlers, Glue Data Catalog, and schema evolution.
    • Build, optimize, and unit test applications on the Apache Spark framework using PySpark.
    • Design and optimize data lakes using Apache Iceberg on AWS, including table compaction and Iceberg performance tuning.
    • Work extensively with data formats such as Avro, Parquet, JSON, XML, and CSV.
    • Orchestrate event-driven workflows using AWS Step Functions and Amazon EventBridge.
    • Connect and integrate Starburst from Lambda and Glue ETL jobs for federated querying.
    • Implement CI/CD pipelines for automated testing and deployment.
    • Perform unit testing using PyTest, and performance tuning of Spark and Python applications

Qualifications

    • Strong understanding of AWS architecture best practices, scalability, security, and cost optimization strategies.
    • Strong hands-on experience with AWS services including Lambda, Glue ETL, Athena, S3, DynamoDB, Step Functions, EventBridge, SNS, and SQS.
    • Deep experience in Apache Spark (PySpark/Scala) development, unit testing, and performance optimization.
    • Strong Python programming skills using libraries such as pandas, requests, json, and awswrangler.
    • Experience on Apache Kafka and Confluent Kafka.
    • Experience designing and optimizing data lakes using Apache Iceberg, including compaction and Iceberg optimization techniques.