Data Platform Engineer - Python - Senior

Montcure LLC

$90K — $115K *
Aerospace & Defense
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Data Engineering, or a related field
  • 4-7 years of experience in data engineering or platform engineering
  • Proficient in developing Python-based data pipelines
  • Experience with ETL/ELT pipelines and data transformation workflows
  • Familiarity with Palantir Foundry or other enterprise data platforms

Responsibilities

  • Develop and maintain Python data pipelines and transformation workflows
  • Build ingestion pipelines for financial management and logistics data
  • Implement transformation logic for raw datasets
  • Support lifecycle management of datasets, including monitoring and validation checks
  • Troubleshoot and resolve pipeline failures

Benefits

  • Remote eligibility for the position
  • Opportunity to work on a significant government project
  • Engagement with advanced data technologies like Palantir Foundry
  • Collaboration with multidisciplinary teams including ontology engineers
  • Gain experience in managing enterprise-level data environments
Full Job Description
Data Platform Engineer (Python) - Senior - Palantir Foundry / Jupyter Platform Support

Location: Washington D.C. (Remote Eligible)

Level: Senior

Clearance: Must be able to attain and maintain a minimum DoW Secret Clearance

*Candidates must have the above clearance level and, at a minimum, be able to maintain this clearance during their employment with Montcure.

Job Summary

The Senior Data Platform Engineer will support development and operation of a modern data environment supporting Navy financial management and audit artifact traceability initiatives. The role focuses on building and maintaining data pipelines, ingestion workflows, and transformation processes within Palantir Foundry and the Jupyter data platform environment. The engineer will work alongside ontology engineers and platforms lead to ingest, transform, and manage datasets that support artifact traceability, audit response reporting, and operational data applications.

Key Responsibilities

Data Pipeline Development:

  • Develop and maintain Python-based data pipelines and transformation workflows within Palantir Foundry and the Jupyter platform.
  • Build ingestion pipelines integrating financial management, logistics, property, and other enterprise datasets.
  • Implement transformation logic to prepare raw datasets for curated data layers and ontology population.


Data Platform Operations:

  • Support dataset lifecycle management including refresh schedules, validation checks, and pipeline monitoring.
  • Troubleshoot pipeline failures and assist in maintaining platform data reliability and stability.
  • Maintain dataset lineage awareness and support platform data integrity practices.


Data Integration and Support:

  • Assist with integrating enterprise system data into the platform environment.
  • Collaborate with ontology engineers to ensure pipelines populate ontology objects and platform data structures correctly.
  • Document pipelines and transformation logic to support maintainability of the platform.


Required Qualifications

Education:

  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related technical field (or equivalent experience).


Experience:

  • 4-7 years experience in data engineering or platform engineering roles.
  • Experience developing Python-based data pipelines
  • Experience building ETL/ELT pipelines and data transformation workflows
  • Experience working with enterprise data platforms such as Palantir Foundry, Databricks, AWS data platforms, or similar distributed data environments
  • Experience integrating datasets from enterprise systems (ERP, financial systems, logistics systems, etc.) preferred


Skills:

  • Strong Python development skills for data processing and pipeline development
  • Experience with SQL and data transformation frameworks
  • Familiarity with distributed data platforms and large-scale data environments
  • Strong troubleshooting and problem-solving skills in data pipeline operations
  • Ability to collaborate with platform engineers, ontology engineers, and functional stakeholders


Status: Contingency - This work is contingent upon award.

Salary Range: $90-$115k per year

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