Department Summary:
Join the “Data Engineering and Environments Department (L146)” in MITRE Labs and build secure, scalable data foundations and solutions across the federal government. Our mission-focused data capabilities include modernizing data ecosystems, enabling secure data access and interoperability, and engineering resilient computing environments. Our team delivers impactful solutions that strengthen national defense and civilian missions, from joint warfighting and cyber defense to public safety and transportation. We turn complex data environments into decisive advantage.
Roles & Responsibilities:
Design, build, and deploy modern data pipelines to support structured, unstructured, streaming, and multimodal mission datasets
Develop and enhance data ingestion, transformation, and integration workflows within distributed data environments
Assist in defining data models, integration patterns, schemas, metadata, and cataloging structures across distributed environments
Help document architecture decisions, trade-off analyses, and blueprint artifacts to support stakeholder communication
Support evaluation of emerging technologies, analytics platforms, and commercial products to align with mission requirements
Conduct exploratory data analysis, feature engineering, and algorithm assessment to support rapid prototyping and mission experimentation
Apply modern Data and AI techniques to automate testing, deployment, and monitoring across development lifecycles
Collaborate with cross-functional teams to translate operational challenges into technical implementation paths
Basic Qualifications:
Requires a Bachelor’s degree and a minimum of 2 years of related experience; or an advanced degree with relevant experience who can immediately contribute at this job step; or equivalent combination of related education and work experience.
Hands-on experience with one or more of the following: Python, SQL, R, or equivalent languages for data retrieval, processing and analysis
Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and analytical tooling
Strong knowledge or experience using one or more of the following modern data technologies such as Containerization, Spark, Databricks, Kafka, Airflow, distributed databases
Good understaning of cloud platforms (AWS, Azure, or GCP) and experience is a plus
Ability to obtain and maintain at least a Secret clearance, which requires U.S. citizenship
This position requires a minimum of 50% hybrid on-site
Preferred Qualifications:
Ability to obtain and maintain a Top Secret/SCI clearance
Experience with ingesting and retrieving data from various databases/sources, visualization and reporting tools such as Power BI, Tableau, or Superset
Experience developing production-grade data or ML pipelines
Ability to build trusted relationships with internal and external mission partners
Experience with system modeling such as use case diagram, class diagrams to represent systems and high-level functions /interactions using any modeling tool is a plus
Knowledge of MLOps/DevSecOps tools, CI/CD workflows, and Containerization
Familiarity with data governance, metadata cataloging, or standards-based interoperability
Strong analytical, problem-solving, communication, and teamwork skills
This requisition requires the candidate to have a minimum of the following clearance(s):
NoneThis requisition requires the hired candidate to have or obtain, within one year from the date of hire, the following clearance(s):
Top SecretSalary compensation range and midpoint:
$80,000 - $100,000 - $120,000 AnnualWork Location Type:
HybridCommitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local or international law.
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