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Momentum Engineering

Designs secure cloud-based data architectures

Data Scientist 3

Data EngineeringConfirmed live in the last 24 hours
Full-timeFort Meade, MD, USA$140k - $185k /yrIn-person

About the Job

Requirements

  • A Master's degree with 6 years of relevant experience, a Bachelor's degree with 8 years of relevant experience, or an Associate's degree with 10 years of in-depth relevant experience clearly related to the position.
  • Active Top Secret/SCI clearance with NSA Full Scope Polygraph is required.
  • Strong Python development experience is required.
  • Strong SQL skills are required.
  • Experience developing extract, transform, and load (ETL) or extract, load, and transform (ELT) workflows is required.
  • Experience performing data preprocessing, validation, filtering, normalization, aggregation, and transformation is required.
  • Experience developing reusable automation solutions is required.

Responsibilities

  • Design and automate reporting and data-processing workflows.
  • Develop scalable ETL processes supporting incremental and batch data ingestion.
  • Perform data transformation, cleansing, validation, aggregation, and reshaping.
  • Develop reusable Python automation packages and scripts.
  • Build and maintain SQL-based data-processing workflows.
  • Support dashboard automation and reporting capabilities.
  • Develop processes that improve data quality and reliability.
  • Document data flows, automation processes, and technical procedures.

Desired Qualifications

  • Experience with Pandas, PySpark, or Polars.
  • Experience developing automated dashboards using Power BI, Tableau, or similar platforms.
  • Experience supporting large-scale or mission-oriented data environments.

About the Company

Momentum Engineering

Designs secure cloud-based data architectures

Momentum Engineering builds secure, cloud-based data engineering solutions that help clients run mission-critical analytics and improve software performance. Its offerings center on designing robust data architectures and data-driven engineering methodologies, implemented through DevOps and DevSecOps practices to ensure reliable, measurable performance. The company differentiates itself by focusing on secure architectures tailored to clients' needs, rigorous evaluation and validation of data-driven approaches, and a client-focused service model with collaborative culture and profit-sharing to attract top talent. The goal is to provide dependable data infrastructure and engineering processes that enable better analytics outcomes and software reliability for engineers, analysts, developers, and instructors.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Columbia, SC
Founded
2015

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