Senior Data Visualization Developer

Description
Essnova Solutions, Inc. is an award-winning SBA 8(a) and HUBZone-certified small business delivering advanced technology and professional services to federal, state, local, and commercial clients. Our expertise spans geospatial, healthcare, and environmental solutions, and we are committed to supporting agencies with high-impact, compliance-driven projects.

We are seeking a Senior Data Visualization Developer to serve as the technical lead for the National Center for Health Statistics (NCHS) visualization and solutions development. This role is pivotal in driving the end-to-end lifecycle of data visualization products, ensuring accuracy, accessibility, and compliance with federal standards. You will architect reusable visualization components, bridge communication between statisticians and developers, and uphold rigorous data validation and accessibility requirements.

Key responsibilities include:

• Lead the technical execution of NCHS visualization and solutions development tasks, overseeing the full development lifecycle from requirements gathering to deployment and documentation.
• Make strategic decisions on visualization tool selection (e.g., Tableau, Power BI, R/Shiny, Python/Dash, D3.js) and architect/build/maintain a reusable component library for NCHS.
• Develop and maintain automated data validation scripts to ensure compliance with statistical accuracy and suppression logic.
• Translate requirements between statisticians and developers by producing implementable specifications, including data models, query patterns, suppression logic rules, and annotated wireframes.
• Conduct and oversee Section 508/WCAG accessibility testing using automated and manual screen reader tools in coordination with project management methodology.
• Provide technical guidance on data architecture, technology risk assessment, and enterprise architecture artifacts, including process and data-flow diagrams.
• Support Adobe Analytics administration and reporting as needed.
• Collaborate closely with Data Engineers and PMs to ensure compliance with federal statistical agency standards and protected data requirements.

Requirements

Required Qualifications:

• Bachelor’s degree in Computer Science, Data Science, Statistics, Information Systems, or a related field
• 7+ years of data visualization development experience in federal agencies or compliance-driven environments
• Advanced proficiency in at least three of the following: Tableau, Power BI, R (ggplot2/Shiny/R Markdown), Python (plotly/Dash/pandas/matplotlib), D3.js, with working proficiency in the remaining tools
• Experience serving as technical lead for end-to-end data visualization development, including requirements, preprocessing, design, build, review, accessibility testing, deployment, and documentation
• Experience presenting statistical data, including confidence intervals, weighted estimates, and suppression rules
• Experience conducting Section 508 / WCAG 2.0 Level AA accessibility testing using automated tools (axe or WAVE) and manual screen reader testing (JAWS or NVDA)
• Proficiency with Git for code reviews and embedded documentation, and SQL for analytics/visualization data needs
• Experience translating requirements between statisticians and developers by producing implementable specifications (data models, query patterns, annotated wireframes)
• Experience administering and reporting with Adobe Analytics or equivalent digital analytics platforms
• Active Tier 4 / High Risk Public Trust (Level 6+) clearance at time of proposal submission and eligibility for HSPD-12/PIV credentialing
• Currently located in the United States and able to overlap core working hours in Eastern Time

Preferred Qualifications:

• Master’s degree in Computer Science, Data Science, Statistics, Information Systems, or a related field
• Experience with NCHS, CDC, or federal statistical data environments
• Experience applying machine learning techniques to analysis or visualization tasks
• Familiarity with HHS EPLC or equivalent federal project lifecycle methodologies