Sr. Systems Engineer

Leidos

20h

About The Position

Leidos’ Defense Systems Sector’s Digital Engineering team is a service-oriented organization that works with programs and project teams to systematically improve efficiency, eliminate and prevent pain points, and bring modern digital practices to the hands of the tactical day-to-day employee. We are responsible for architecting and implementing large-scale Digital solutions, independent reviews of digital practices, and support of teams implementing new practices. The team plays a pivotal role in fostering teamwork, creativity, and technological advancement in digital engineering initiatives, driving competitive advantage and value creation for the organization. Our Applied Digital Engineering @Leidos (A-DEAL) needs a Data Analytics to work primarily with our AI Integration team, Data Engineers, and Software Engineers to guide the design and implementation of an engineering metrics dashboard used to perform AI-assisted, trade space. Primary skills require comfort with modeling and graphing data and recommending the best form of data visualization based on the available data and stakeholder use cases. Must be a proactive, motivated problem solver and comfortable with working in a research environment. Knowledge of Agentic AI and common MLOps pipeline tools is beneficial but not required. Primary Responsibilities: •This role is responsible for leading analytics initiatives, translating business and mission needs into actionable insights, and mentoring data engineering team while remaining hands-on with data. The ideal candidate combines strong technical expertise with leadership, stakeholder engagement, and strategic thinking. •Ability to work both independently and in a collaborative team environment by partnering with AI Integration teammates, Data Scientists, and Developers across organizational boundaries •Ability to develop solutions in a rapid prototyping environment and for production •Ability to adapt and learn new tools and languages as needed to devise software solutions •Understands Full data lifecycle, from planning, acquisition/ingest through visual display in a metrics dashboard environment •Some Application and data layer programming •Developing and implementing ETL processes in a cloud-based AWS environment (data extraction, parsing, cleansing/curation, translation/transformation, tagging, loading, replication, and distribution) •Hands-on Systems and/or Digital Engineering experience

Requirements

12yrs with a Bachelor’s degree in Systems Engineering, Software Engineering, or a related field. Additional years experience may be used in lieu of a degree.
Familiarity with engineering tools and software such as MATLAB, Simulink, Cameo, or similar.
Strong problem-solving skills and a desire to learn and adapt as facts or decisions are determined.
Excellent written and verbal communication skills, with the ability to work collaboratively in a team.
Ability to obtain and maintain a DoD Secret clearance.

Nice To Haves

Active DoD Secret clearance or higher.
+8 years of experience in engineering, systems modeling, or software development (internships or academic projects acceptable).
Basic understanding of digital engineering concepts, model-based systems engineering (MBSE), and systems lifecycle management.
Experience on a model-driven program that implemented Digital Engineering concepts.
Experience with creating technical documentation.
Familiar with Agile, CI/CD, Git, Gitlab, Microsoft coding tools.
Familiar with high-tech research and development projects.

Responsibilities

This role is responsible for leading analytics initiatives, translating business and mission needs into actionable insights, and mentoring data engineering team while remaining hands-on with data. The ideal candidate combines strong technical expertise with leadership, stakeholder engagement, and strategic thinking.
Ability to work both independently and in a collaborative team environment by partnering with AI Integration teammates, Data Scientists, and Developers across organizational boundaries
Ability to develop solutions in a rapid prototyping environment and for production
Ability to adapt and learn new tools and languages as needed to devise software solutions
Understands Full data lifecycle, from planning, acquisition/ingest through visual display in a metrics dashboard environment
Some Application and data layer programming
Developing and implementing ETL processes in a cloud-based AWS environment (data extraction, parsing, cleansing/curation, translation/transformation, tagging, loading, replication, and distribution)
Hands-on Systems and/or Digital Engineering experience