The Leidos Digital Modernization Sector is seeking an experienced Data Product Lead; this position will allow for full time telework from any U.S. based location.
POSITION SUMMARY:
The Data Product Lead will drive the design, and delivery of high-value data products that enable advanced analytics, AI/ML, and agentic AI use cases. This role requires a product development mindset, with a strong ability to balance business priorities, user needs, and technical capabilities and will serve as the bridge between functional data product owners, business stakeholders, and technical teams (data engineering, data science, data architecture, and governance). They will be accountable for ensuring data products are well-defined, user-focused, and delivered with measurable impact on business outcomes.
PRIMARY RESPONSIBILITIES:
- Partner with functional team leadership to co-own the vision, roadmap, and success criteria for specific data products that support business operations, AI/ML, and agentic AI solutions.
- Collaborate with functional data product owners to capture business needs and translate them into technical requirements.
- Coordinate technical staff (data engineers, architects, data scientists, governance specialists) to deliver scalable, reliable, and AI-ready data products.
- Ensure alignment of data products with enterprise data architecture, governance, and quality standards.
- Partner with Data Scientists and AI Engineers to ensure data products support advanced ML, GenAI, and agentic AI use cases (e.g., enabling RAG pipelines, semantic search, or autonomous agents).
- Apply a product development mindset, focusing on usability, reusability, adoption, and measurable business value.
- Track and report on product performance, usage, and ROI, adjusting roadmaps as needed.
- Act as a champion for data products, promoting awareness, adoption, and training across the organization.
- Drive continuous improvement by incorporating feedback loops from business users and technical teams.
- Contribute to the development of data product standards, documentation, and playbooks.
BASIC QUALIFICATIONS:
- Bachelor’s degree in Data Science, Computer Science, Information Systems, Business, or related field, with 8+ years of relevant experience; additional years of experience may be substituted in lieu of a degree.
- Proven experience in product management or product leadership, ideally with data or analytics platforms.
- Strong understanding of data platforms and pipelines (e.g., Snowflake, Informatica, Immuta, Collibra, cloud data services).
- Familiarity with AI/ML concepts and how data products enable advanced AI solutions.
- Excellent skills in requirements gathering, backlog management, and stakeholder engagement.
- Ability to coordinate cross-functional technical teams (engineering, architecture, governance, science).
- Strong business acumen and ability to translate business needs into technical data product requirements.
- Excellent communication
- US citizenship required.
PREFERRED QUALIFICATIONS:
- Experience with data mesh or data product-oriented architectures.
- Exposure to Generative AI and agentic AI use cases, particularly how they leverage structured, unstructured, and semi-structured data.
- Knowledge of data governance, compliance, and security principles.
- Familiarity with agile product development practices and tools (Jira, Confluence, Azure DevOps).
- Experience working in regulated industries (finance, healthcare, defense, government).
- Certifications in product management, agile practices, or data platforms (e.g., Certified Scrum Product Owner, Pragmatic Institute, Snowflake, Collibra)
At Leidos, we don’t want someone who "fits the mold"—we want someone who melts it down and builds something better. This is a role for the restless, the over-caffeinated, the ones who ask, “what’s next?” before the dust settles on “what’s now.”
If you’re already scheming step 20 while everyone else is still debating step 2… good. You’ll fit right in.
Original Posting:October 20, 2025For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
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