The U.S. Social Sector, Healthcare, and Public Sector Entities (SHaPE) practice, specifically within the Defense and Security subsector, is looking to solve complex and pressing challenges for clients within the U.S. Department of Defense (DoD) and the National Security Community. The role aims to design and develop core data frameworks to drive meaningful mission outcomes by enabling software capabilities for various users, shifting towards asset-based consulting and fostering an entrepreneurial culture.
Requirements
- Ability to write clean, maintainable, scalable, and robust code in an object-oriented language
- Proven experience building data pipelines in production for advanced analytics use cases. Experience working across structured, semi-structured, and unstructured data
- Extensive experience with graph data structures, common graph databases (e.g., Neo4j, Janus), and query languages (e.g., Cypher, Gremlin)
- Demonstrated ability to apply graph analytics in modeling complex system relationships and workflows
- Extensive experience designing or integrating models that represent complex, time-dependent workflows or processes, including capturing interdependencies and conditional logic.
- Familiarity with distributed computing frameworks, cloud platforms, containerization, and analytics libraries
- Experience with event streaming or real-time data processing to support analysis of high velocity, sequential data flows
Responsibilities
- design and develop core data frameworks to drive meaningful mission outcomes for our clients by enabling software capabilities used by data engineers, data scientists, consulting teams and external clients.
- work in cross-functional Agile project teams alongside data scientists, machine learning engineers, other data engineers, project managers, and industry experts to innovate alongside clients and CSTs to develop new or existing assets.
- leverage engineering frameworks and best practices.
- build a foundation for the expansion of our investment into our entrepreneurial culture.
- write clean, maintainable, scalable, and robust code in an object-oriented language.
- build data pipelines in production for advanced analytics use cases.
- apply graph analytics in modeling complex system relationships and workflows.
Other
- Active TS/SCI clearance (or SCI-eligbility), ideally with past or current DoD SAP/SAR access
- Advanced degree in a quantitative field like computer science, machine learning, applied statistics or mathematics; or equivalent experience
- 7-8 years of relevant experience; familiarity with aerospace and defense program and/or mission data preferred
- Practical knowledge of software engineering concepts and best practices, inc. DevOps, DataOps, and MLOps would be considered a plus
- Proven ability to align data engineering approaches with large-scale interconnected systems, while engineering solutions to remain adaptable under changing conditions
