Data Engineer - Contract - Onsite

Data Engineer

Key Responsibilities

• Design, build, and maintain robust and scalable data pipelines for ingesting and transforming large volumes of structured, semi-structured, and geospatial data using PySpark and PySpark GIS.
• Enhance platform automation, orchestration, monitoring, and alerting to improve system reliability and developer efficiency.
• Implement end-to-end

  ETL workflows

  and support data lake architecture and big data processing.
• Partner with engineering, product, and business teams to deliver high-quality, production-ready datasets and services.
• Continuously identify and implement improvements for pipeline efficiency, automation, and usability.
• Support platform users by providing technical assistance and clear documentation.
• Define and maintain best practices for data quality, observability, and operational excellence.

Required Qualifications

• 3+ years

  of professional experience in

  data engineering

  .
• Expert-level knowledge of

  Python

  ,

  SQL

  , and

  PySpark

  .
• Solid experience in

  building data pipelines

  ,

  ETL development

  , and working with

  data lakes

  and

  big data frameworks

  .
• Hands-on experience with AWS cloud services for data engineering (such as S3, EMR, Glue, Lambda, or Redshift).
• Demonstrated ability to collaborate with cross-functional teams in a distributed engineering environment.
• Hands-on experience with version control and CI/CD workflows (Git, GitLab, Bitbucket, etc.).
• Familiarity with platform monitoring and alerting best practices.

Nice to Have

• Experience with

  Palantir Foundry

  or similar enterprise data platforms.
• Knowledge of cloud-based data architectures, AWS services, and infrastructure-as-code.
• Experience with geospatial data processing and analytics using PySpark GIS.

Why Join

• Contribute to a critical data transformation effort for a major US utility provider.
• Work in a fast-paced environment with

  opportunities for career growth and development

  .
• Engage in meaningful, hands-on engineering with modern data infrastructure and tooling.