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Lead Data Engineer

Role overview

Qualifications

  • At least 5 years of applicable professional background
  • A minimum of one year spent leading and managing development teams
  • Solid foundation in core Python programming applied to data engineering work
  • Strong capability with PySpark for handling large-scale distributed data processing

Responsibilities

  • Create, construct, and sustain scalable data pipelines running on AWS infrastructure
  • Build dependable data processing solutions leveraging Python, Pandas, and PySpark
  • Establish and oversee workflows via AWS Managed Workflows for Apache Airflow (MWAA)
  • Craft and fine-tune data queries through AWS Athena to enable efficient analytical work

Key facts

Hard skills

Other skills

  • Troubleshooting (Problem Solving)
  • Problem Solving

About the company

EPAM Systems logo

EPAM Systems

  • IT Services & Consulting
  • XLarge
  • 10,001+
Since 1993, EPAM Systems, Inc. (NYSE: EPAM) has used its software engineering expertise to become a leading global provider of digital engineering, cloud and AI-enabled transformation services, and a leading business and experience consulting partner for global enterprises and ambitious startups. We address our clients’ transformation challenges by fusing EPAM Continuum’s integrated strategy, experience and technology consulting with our 30+ years of engineering execution to speed our clients’ time to market and drive greater value from their innovations and digital investments. We make GenAI real with our AI LLM orchestration, testing and engineering solutions, EPAM DIAL, EPAM EliteA™ and EPAM AI/RUN™, respectively. We deliver globally, but engage locally with our expert teams of consultants, architects, designers and engineers, making the future real for our clients, our partners and our people around the world. We believe the right solutions are the ones that improve people’s lives and fuel competitive advantage for our clients across diverse industries. Our thinking comes to life in the experiences, products and platforms we design and bring to market. Added to the S&P 500 and the Forbes Global 2000 in 2021 and recognized by Glassdoor and Newsweek as a Top 100 Best Workplace, our multidisciplinary teams serve customers across six continents. We are proud to be among the top 15 companies in Information Technology Services in the Fortune 1000 and to be recognized as a leader in the IDC MarketScapes for Worldwide Experience Build Services, Worldwide Experience Design Services and Worldwide Software Engineering Services. Learn more at www.epam.com.

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Job description

We're seeking a hands-on Lead Data Engineer to construct and maintain scalable data pipelines along with cloud-based data solutions. The right person for this role brings substantial background in Python, PySpark, AWS, Airflow, and DevOps, with particular attention to production-grade engineering and automation practices Responsibilities Create, construct, and sustain scalable data pipelines running on AWS infrastructure Build dependable data processing solutions leveraging Python, Pandas, and PySpark Establish and oversee workflows via AWS Managed Workflows for Apache Airflow (MWAA) Craft and fine-tune data queries through AWS Athena to enable efficient analytical work Streamline infrastructure setup and deployment workflows through automation using Terraform and GitHub Actions Put in place testing, monitoring, troubleshooting practices, and data-quality safeguards to keep pipelines dependable Take part in reviewing code and help promote sound engineering practices throughout the team Work alongside engineering, product, and business groups within an Agile setting Requirements At least 5 years of applicable professional background A minimum of one year spent leading and managing development teams Solid foundation in core Python programming applied to data engineering work Practical experience applying Python Pandas for manipulating and analyzing data Strong capability with PySpark for handling large-scale distributed data processing Background working with AWS MWAA or Apache Airflow to coordinate and manage data workflows Familiarity with AWS Athena for running queries and analyzing data housed within AWS Hands-on background using Terraform to automate infrastructure setup and management Working knowledge of GitHub Actions for constructing automated CI/CD pipelines Good grasp of DevOps principles as applied within data engineering contexts Strong capabilities in data engineering, troubleshooting, and resolving complex problems Upper-intermediate English language skills or higher (B1) Nice to have Background applying GitHub Copilot to assist with development, code reviews, testing, and release processes Knowledge of CI/CD methodologies and associated tools for smoother software delivery Background working within Agile/Scrum team structures Experience gained within financial services or investment management sectors Background in Gen AI application development and incorporating Gen AI practices into the software development lifecycle (SDLC)

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