Overview

We are seeking an experienced Senior Data Engineer with expert-level skills in PySpark and hands-on experience building ETL pipelines, data lake architectures, and data feed integrations on AWS to join our team. You will work with both structured and unstructured data, ingesting from multiple on-premises and enterprise data sources such as SAP, Intelex, SQL, and OSI PI into AWS. This role offers the opportunity to contribute to large-scale data solutions and collaborate with cross-functional teams in a dynamic environment.

Responsibilities

  • Design, develop, and optimize ETL pipelines using PySpark and AWS Glue Jobs to process large volumes of structured and unstructured data
  • Orchestrate data workflows with Apache Airflow, ensuring reliable scheduling, dependency management, and robust error handling
  • Build and maintain data feeds from on-premises and enterprise systems into AWS data lake environments
  • Integrate with enterprise data sources including SAP for ERP and operational data, Intelex for environmental, health, safety, and quality data, SQL databases for relational data, and OSI PI for real-time industrial and process historian data
  • Develop and manage API interactions to extract data from on-premises services into AWS
  • Handle data extraction, transformation, and loading across various formats and protocols
  • Support the design and maintenance of AWS data lake architectures using Amazon S3, AWS Glue, and Lake Formation
  • Ensure data is cataloged, partitioned, and optimized for analytics and reporting
  • Implement data quality checks, validation, and lineage tracking across all pipelines

Requirements

  • Minimum 3 years of experience in data engineering roles
  • Advanced proficiency in Python and PySpark for data processing and pipeline development
  • Strong background in Extract, Transform, Load (ETL) processes
  • Experience orchestrating workflows with Apache Airflow
  • Proven track record building production-grade data pipelines on AWS
  • Hands-on experience with AWS Glue Jobs for ETL processing
  • Familiarity with Amazon S3, data lake patterns, and data cataloging techniques
  • Experience using AWS-native monitoring and operational tools
  • Skilled in integrating with enterprise systems via APIs, JDBC, or native connectors, including SAP, Intelex, SQL databases, and OSI PI
  • Ability to work with both structured and unstructured data formats
  • Excellent documentation, communication, and collaboration skills
  • English communication skills at B2+ level or higher, both written and spoken

Nice to have

  • Familiarity with energy, oil & gas, or industrial data environments
  • Understanding of Drilling and Completions data flows and terminology

[GTS] Benefits (generic, except India)

  • International projects with top brands
  • Work with global teams of highly skilled, diverse peers
  • Healthcare benefits
  • Employee financial programs
  • Paid time off and sick leave
  • Upskilling, reskilling and certification courses
  • Unlimited access to the LinkedIn Learning library and 22,000+ courses
  • Global career opportunities
  • Volunteer and community involvement opportunities
  • EPAM Employee Groups
  • Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn