Lead Data Engineer

Capgemini

Chicago, IL, US
Base: 160,000- 220,000; bonus/equity: not specifie...
On-site
Palantir foundry platform mastery
Pyspark, spark sql, and python proficiency
Ontology-aware application development
Design, build, and maintain end-to-end ETL/ELT pipelines using PySpark, Spark SQL, and Python

Job Summary

  • Design, build, and maintain end-to-end ETL/ELT pipelines using PySpark, Spark SQL, and Python.
  • Configure and manage data connections, Pipeline Builder, and Contour for data exploration and visualization.
  • Partner with data scientists, analysts, and business stakeholders to translate requirements into scalable data solutions.

Matching Summary

Design, build, and maintain end-to-end ETL/ELT pipelines using PySpark, Spark SQL, and Python.

Salary

Base: 160,000- 220,000; Bonus/Equity: Not specified; Benefits: Comprehensive, non-negotiable benefits package

Skills & Requirements

Must-have

  • Palantir Foundry platform mastery
  • PySpark, Spark SQL, and Python proficiency
  • Ontology-aware application development
  • ETL/ELT pipeline design and maintenance
  • Data cleansing, transformation, and validation

Nice-to-have

  • Familiarity with Generative AI (GenAI)
  • Cloud platform experience (e.g., Azure)
  • Snowflake integration knowledge

Key Requirements

  • 8+ years of experience in data engineering
  • Deep hands-on experience with Palantir Foundry
  • Solid understanding of data modeling
  • Proven ability to troubleshoot complex data issues

Work Rights

Not specified

Tailored Resume

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