Principal Data Engineering and Management Specialist

at  THE MITRE CORPORATION

Why choose between doing meaningful work and having a fulfilling life? At MITRE, you can have both. That’s because MITRE people are committed to tackling our nation’s toughest challenges—and we’re committed to the long-term well-being of our employees. MITRE is different from most technology companies. We are a not-for-profit corporation chartered to work for the public interest, with no commercial conflicts to influence what we do. The R&D centers we operate for the government create lasting impact in fields as diverse as cybersecurity, healthcare, aviation, defense, and enterprise transformation. We’re making a difference every day—working for a safer, healthier, and more secure nation and world. Our workplace reflects our values. We offer competitive benefits, exceptional professional development opportunities, and a culture of innovation that embraces diversity, inclusion, flexibility, collaboration, and career growth. If this sounds like the choice you want to make, then choose MITRE—and make a difference with us.

DEPARTMENT SUMMARY:

Are you a trailblazer in the realm of data engineering and management, impassioned to spearhead solutions and address intricate challenges? The Data Environments and Engineering Department (L176) within the Data and Human Centered Solutions Innovation Center is seeking a visionary individual to join us as a Principal Data Engineering and Management Specialist. We are in search of candidates with a robust background in both data engineering and data management, coupled with an unwavering commitment to harnessing data for informed decision-making and critical mission processes.

BASIC QUALIFICATIONS:

• 12 years of related experience with a Bachelor’s degree; or 8 years and a Master’s degree; or a PhD with 6 years experience; or equivalent combination of related education and work.
• Capable of obtaining and maintaining a DoD clearance.
• Experience leading technical teams in data-oriented solutions.
• Proven experience identifying and harnessing business opportunities, and securing needed resources.
• Demonstrated expertise in one or more areas of data management, data science, and/or data engineering.
• Hands-on experience with one or more database technologies (e.g., PostgreSQL, Oracle, MySQL, SQL Server, DB2, MongoDB, Neo4j, Couchbase, Cassandra).
• Excellent written and verbal communications skills with ability to prepare, describe and present complex technical concepts in relatable terms.
• Strong knowledge of ETL/ELT processes, tools, and frameworks.
• Experience with large scale data architectures. Activities may include analysis of alternatives, technical product evaluations, requirements analysis, design, data systems prototyping, and process automation.
• Experience building conceptual, logical, and physical data models.
• Knowledge of cloud platforms and technologies such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
• Data Engineering skills to include:
• Experience with preparing data for analysis
• Strong understanding of data science concepts
• Experience with BI tools
• Understanding ML frameworks, algorithms, and libraries
• Understanding of cybersecurity principles and best practices, with the ability to integrate security measures into data management solutions.
• Strong innovation, problem-solving, systems analysis, planning, organizational, and interpersonal skills.
• Experience leading or supporting business development and/or work-shaping efforts, such as identifying new business opportunities, preparing business proposals, and defining or expanding work for customers.
• Knowledge of data management practices across the full data life cycle, such as data strategy, requirements, design and development, data science, data governance, metadata management, data quality, business intelligence, and data security & privacy.
• Knowledge of and experience across the full system development life cycle.
• Desire to continuously learn new techniques and evolve approaches by regularly engaging in structured educational pursuits, personal research, and outreach to subject matter experts across the corporation.
• This position requires a minimum of 50% hybrid on-site.

PREFERRED QUALIFICATIONS:

• Master’s degree or PhD in computer science, data science, systems engineering, software engineering, engineering, or information systems.
• Proven experience in trusted advisor roles to senior internal/external leaders.
• Repeated experience shaping solutions and building/leading technical teams for complex business objectives.
• Experience migrating legacy data systems to new/modernized platforms.
• Hands-on experience with data flow and pipeline frameworks such as Kafka, NiFi, Spark, Airflow, and Hadoop, and experience performing source to target data mapping.
• Designing and building prototypes for ingesting, curating, and analyzing data at scale.
• Familiarity with microservice architectures, data warehousing, data fabric, data lakes, and data mesh, and non-relational database architectures (i.e., NoSQL).
• Applied mathematics: probability and statistics.
• Understand the use of data and governance in AI/ML and LLM.
• Experience with artificial intelligence, large language models, machine learning, and natural language processing techniques.
• Existing DoD Clearance.

Working with experienced project teams and data management experts, project tasks may include:

• Planning and leading the development of high quality, high velocity contributions to sponsor challenges and deliverables.
• Leading projects and/or major project tasks, including supervising the work of other staff, applying best practices in project/task management and staff development, and defining project approaches/methodologies to complete project deliverables.
• Collecting and preparing data for use by data scientists and analysts.
• Leading stakeholder interviews to determine data requirements and define data flows.
• Guiding state-of-the art data transformations to meet the requirements for system interfaces and data integration projects.
• Performing data profiling to identify quality gaps and determine if data is fit for use for its intended purpose.
• Researching and evaluating data engineering tools and technologies.