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Posted 2 days ago

Open

Data Engineer

Chantilly, VARemote

AI Summary

Fantom Corporation is a mission-focused organization supporting critical programs across the defense and intelligence community. We partner with our customers to deliver high-impact technical solutions while fostering a culture built on trust, expertise, and long-term career growth.

About this role

Fantom Corporation is a mission-focused organization supporting critical programs across the defense and intelligence community. We partner with our customers to deliver high-impact technical solutions while fostering a culture built on trust, expertise, and long-term career growth.

We are seeking a Data Engineer to support the development and optimization of enterprise data pipelines and ETL workflows. This role is responsible for extracting, transforming, and loading structured and unstructured data from a variety of sources into centralized data platforms. The ideal candidate has strong experience with Python, SQL, and Palantir or similar ETL platforms, along with a passion for building scalable, high-quality data solutions.

This position offers the opportunity to work on mission-critical data initiatives, collaborating with technical and business stakeholders to deliver reliable, high-performance data products that drive operational and analytical decision-making.

Responsibilities

  • Design, develop, and maintain scalable ETL pipelines using Python, SQL, and Palantir or similar data integration platforms
  • Extract, transform, and load structured and unstructured data from databases, APIs, flat files, and other enterprise data sources
  • Develop robust Python scripts and SQL queries to automate data ingestion, transformation, and processing workflows
  • Design and implement data models that support analytics, reporting, and operational requirements
  • Optimize data structures, queries, and pipelines for performance, scalability, and reliability
  • Perform data cleansing, validation, and quality assurance to ensure data accuracy and consistency
  • Develop data enrichment and transformation workflows to improve data usability
  • Monitor ETL processes and implement automated quality checks and error handling
  • Collaborate with engineers, analysts, and business stakeholders to gather requirements and deliver data solutions
  • Provide technical guidance and best practices for data engineering tools and platforms, including Palantir
  • Document data pipelines, workflows, and technical processes to support ongoing operations and maintenance
  • Required Qualifications

  • Must be fully cleared with a recent polygraph
  • Must be willing and able to work fully onsite at the location listed in this posting
  • 3+ years of experience in Data Engineering or a related technical field
  • Strong programming experience with Python
  • Advanced SQL skills, including query development, optimization, and data transformation
  • Experience with ETL development and data integration platforms such as Palantir or similar technologies
  • Experience integrating data from APIs, relational databases, flat files, and other enterprise data sources
  • Strong understanding of structured and unstructured data processing
  • Experience implementing data quality, validation, and monitoring processes
  • Excellent analytical, troubleshooting, and problem-solving skills
  • Strong communication and collaboration skills with both technical and non-technical teams
  • #CJ
  • Desired Qualification

    • Bachelor's degree in Computer Science, Data Engineering, or a related technical discipline
    • Hands-on experience with Palantir Foundry or other Palantir platforms
    • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP)
    • Experience with big data technologies such as Apache Spark or Hadoop
    • Experience with workflow orchestration tools such as Apache Airflow, Prefect, or similar platforms
    • Experience building scalable enterprise data pipelines and analytics platforms
    • Familiarity with modern data engineering best practices and cloud-native architectures

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