Overview

We are seeking an experienced Lead Data Engineer with advanced expertise in PySpark and hands-on experience building ETL pipelines, data lake architectures, and integrating data feeds on AWS.

You will handle both structured and unstructured data, ingesting information from a variety of on-premises and enterprise sources such as SAP, Intelex, SQL, and OSI PI into AWS. This position provides the chance to work on large-scale data projects and collaborate with diverse teams in a fast-paced setting.

Responsibilities

  • Create, refine, and manage ETL pipelines using PySpark and AWS Glue Jobs to process extensive structured and unstructured datasets
  • Coordinate data workflows with Apache Airflow, ensuring dependable scheduling, dependency management, and effective error handling
  • Develop and sustain data feeds from on-premises and enterprise systems into AWS data lake environments
  • Integrate with enterprise 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
  • Build and oversee API interactions to retrieve data from on-premises services into AWS
  • Manage data extraction, transformation, and loading across multiple formats and protocols
  • Assist in designing and maintaining AWS data lake architectures using Amazon S3, AWS Glue, and Lake Formation
  • Ensure data is properly cataloged, partitioned, and optimized for analytics and reporting
  • Apply data quality checks, validation, and lineage tracking throughout all pipelines

Requirements

  • At least 5 years of experience in data engineering positions
  • Minimum one year of experience leading and managing development teams
  • High-level proficiency in Python and PySpark for data processing and pipeline creation
  • Strong foundation in ETL processes for data integration
  • Experience coordinating workflows with Apache Airflow
  • Demonstrated success building production-grade data pipelines on AWS
  • Hands-on experience with AWS Glue Jobs for ETL operations
  • Familiarity with Amazon S3, data lake methodologies, and data cataloging practices
  • Experience with AWS-native monitoring and operational tools
  • Skilled in integrating enterprise systems via APIs, JDBC, or native connectors, including SAP, Intelex, SQL databases, and OSI PI
  • Capability to work with both structured and unstructured data formats
  • Excellent skills in documentation, communication, and collaboration
  • English proficiency at B2+ level or higher, both written and spoken

Nice to have

  • Experience working with energy, oil & gas, or industrial data environments
  • Knowledge 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