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Data Engineer - Delta Point with Security Clearance

Delta Point LLCSouthern Md Facility, MD🇺🇸United StatesPosted 6 Aug 2026

Quick Overview

Seniority
Mid Senior
Employment type
Employee
Work mode
Hybrid
Location
Southern Md Facility, MD, United States
Posted
3 weeks ago
ETLGitPython

Job Description

Delta Point is seeking a Data Engineer to support the development and maintenance of enterprise data solutions. This role focuses on designing, building, and optimizing back-end data pipelines that transform raw data into curated, business-ready data assets. The ideal candidate has hands-on experience building ETL/ELT pipelines, integrating data from multiple enterprise systems, and delivering scalable data solutions.

Key Responsibilities

  • Design and maintain automated ETL/ELT data pipelines.
  • Integrate data from multiple enterprise systems while ensuring data quality and integrity.
  • Develop Python-based data processing and automation solutions.
  • Build curated data sources supporting finance, supply chain, HR, operations, and other business functions.
  • Collaborate with stakeholders to define requirements and deliver scalable solutions.
  • Document data architectures, workflows, and engineering processes.
  • Support enterprise data platforms, including Palantir and ERP systems. Requirements
  • Bachelor's degree in a related field or equivalent experience.
  • Active Secret Security Clearance
  • 3+ years of professional experience building ETL/ELT pipelines and back-end data solutions.
  • Strong proficiency in Python for data engineering and automation.
  • Experience with low-code ETL/data integration tools.
  • Manage code and deployments using Git/GitHub best practices.
  • Strong analytical and problem-solving skills.

Preferred Qualifications

  • Hands-on experience with Palantir Foundry or similar enterprise data integration platforms.
  • Experience working with SAP, ERP, or related enterprise data structures.
  • Knowledge of modern data architecture and governance principles.
  • Experience supporting finance, supply chain, HR, logistics, or operational data domains.
  • Experience transforming complex enterprise data into curated business-ready datasets.

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