Data Visualization Engineer

The Leidos Digital Modernization Sector is seeking an experienced Data Visualization Engineer; this position will allow for full time telework from any U.S. based location.

POSITION SUMMARY:
The Data Visualization Engineer will design and deliver compelling dashboards, reports, and interactive visualizations that bring data products to life. This role will collaborate with Data Product Leads, Data Scientists, Platform Engineers, and functional business owners to translate raw data into clear, actionable insights and will not only build traditional BI assets but also work with AI/ML and agentic AI teams to create next-generation visual experiences that incorporate structured and unstructured data, semantic search, and LLM-driven insights. . 

PRIMARY RESPONSIBILITIES: 

• Design and develop dashboards, reports, and visualizations using BI and analytics tools (e.g., Tableau, Power BI, Qlik, or equivalent). 
• Partner with Data Product Leads and functional owners to understand use cases and define visualization requirements aligned with business needs. 
• Work closely with Data Scientists and AI Engineers to visualize outputs from ML models, GenAI, and agentic AI systems (e.g., showing confidence scores, agent decision paths, or conversational summaries). 
• Build interactive data exploration tools that help users navigate structured, semi-structured, and unstructured datasets. 
• Apply data storytelling principles to ensure clarity, usability, and business impact. 
• Optimize dashboards for performance, scalability, and usability across the enterprise. 
• Develop visualization standards, style guides, and reusable templates to support consistency across data products. 
• Integrate with AI platforms and APIs to embed LLM-powered insights (e.g., natural language querying, narrative summaries, AI copilots). 
• Collaborate with data platform engineers to ensure underlying data pipelines and governance support visualization needs. 
• Stay current with emerging visualization and human-AI interaction trends, and recommend new approaches to enhance user experience. 

BASIC QUALIFICATIONS:

• Bachelor’s degree in Data Science, Computer Science, Information Systems, or related field, with 8+ years of relevant experience; additional years of experience may be substituted in lieu of a degree.  
• Proven experience with data visualization tools mainly PowerBI. 
• Strong ability to translate business requirements into intuitive visual solutions. 
• Familiarity with SQL, Python, or R for data preparation and visualization scripting. 
• Experience working with structured and semi-structured data (relational, JSON, APIs). 
• Understanding of AI/ML concepts and how to present model-driven insights to end-users. 
• Excellent communication, design sense, and ability to explain data through storytelling. 
• Must be a US citizen. 

PREFERRED QUALIFICATIONS:

• Experience visualizing unstructured data outputs (e.g., documents, text, embeddings, vector databases). 
• Familiarity with agentic AI systems and how to represent agent actions, reasoning, and outputs visually. 
• Experience with data platforms and governance tools (Snowflake, Informatica, Collibra, Immuta). 
• Proficiency in JavaScript frameworks (e.g., D3.js, Plotly, Dash) for custom visualization development. 
• Experience embedding visualizations into AI/ML applications, portals, or chat interfaces. 
• Exposure to natural language query interfaces (BI with conversational AI). 
• Design background or training in UX/UI for data applications. 
• Certifications in Power BI.
   

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.

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.