Data Engineer — TS/SCI Big Data & AI Pipelines

ManTech; Chantilly (NC); On-site; USD 115,000 - 190,000; Full time

Job summary

ManTech in Chantilly, VA is seeking a Data Engineer to join our team on TS/SCI w/ Poly clearance. You will design, ingest, cleanse, transform, and display large data sets, leveraging big data technologies and RESTful APIs.

You will work with data scientists to build pipelines for AI/ML workflows, optimize the data lifecycle, and collaborate with cross-functional teams to deliver scalable data solutions.

Qualifications

• High School Diploma with 4+ years of relevant data engineering, software development, and/or programming experience.
• Experience with Python or Java for data processing and analytics.
• Significant experience with SQL and database management.
• Experience with the full data lifecycle, from ingest through display, in a Big Data environment.
• Hands-on experience with Java-related technologies, such as JDK, J2EE, EJB, JDBC, and/or Spring.
• Experience with RESTful APIs, data pipelining systems like Apache Airflow, and performing ETL tasks in a Linux environment.

Responsibilities

• Design, implement, and optimize data extraction, cleansing, transformation, loading, and large-scale ingest systems.
• Optimize data lifecycle from planning to display and beyond.
• Develop data pipelines and code to ingest and exploit new data sources.
• Develop data profiling, deduping, and matching logic for analysis.
• Collaborate with data scientists to craft AI/ML pipelines and document data layers.
• Work with teammates, vendors, and users to improve data processing methods.

Skills

Data analysis

Programming

Tools

Python

Java

SQL

Apache Airflow

ETL

Linux

Job description

ManTech in Chantilly, VA is seeking a Data Engineer to join our team on TS/SCI w/ Poly clearance. You will design, ingest, cleanse, transform, and display large data sets, leveraging big data technologies and RESTful APIs.

You will work with data scientists to build pipelines for AI/ML workflows, optimize the data lifecycle, and collaborate with cross-functional teams to deliver scalable data solutions.