Senior Data Integration & Decision Support Engineer

Ironclad Defense Works•Norfolk, VA

1d•$120,000 - $140,000•Onsite

About The Position

Ironclad Defense Works is seeking a Senior Data Integration & Decision Support Engineer to support NATO Allied Command Transformation in Norfolk, Virginia. This is a hands-on technical delivery position focused on modernizing fragmented program data, developing reusable data integrations, improving digital data collection, and creating analytical solutions that directly support program and portfolio decision-making. The successful candidate will work directly with operational users, program managers, analysts, portfolio staff, and data owners to personally design, build, test, document, and improve working data and analytical solutions. This position is not primarily an advisory, architecture, management, or supervisory role. The individual must be able to demonstrate recent hands-on technical delivery across the full solution lifecycle, from requirements elicitation and data preparation through development, user testing, operational use, documentation, and transition.

Requirements

Bachelor’s degree in Data Science, Computer Science, Information Systems, Engineering, Operations Research, Statistics, Applied Mathematics, or a closely related field; or at least five years of directly relevant professional experience in lieu of the degree.
Experience-in-lieu candidates must have worked in at least two of the following areas: data integration/data engineering, analytical programming, or business intelligence/analytics/decision-support development.
Demonstrated recent experience personally developing operational data or analytical solutions from user or decision requirement through data preparation, solution development, user testing, and operational use.
At least 12 months within the past 24 months in which hands-on technical delivery was a regular part of assigned work.
At least one personally developed data or analytical solution that has been used by an identifiable user group in an active business or decision-making process within the past 18 months.
At least three years of data integration or data-engineering experience within the past five years, including hands-on experience within the past 24 months.
Demonstrated experience integrating data from at least two separately administered systems, databases, services, or authoritative data sources.
At least two years of recent SQL experience and hands-on use of at least one analytical programming language such as Python, R, Scala, Julia, SAS, MATLAB, Stata, or equivalent.
Recent personal use of both SQL and a qualifying analytical programming language. The SOW specifically excludes DAX, Power Query M, VBA, Excel formulas, and similar expressions from satisfying the analytical-programming requirement.
Experience personally designing or developing at least two digital data-collection, workflow, low-code/no-code, configured-application, or comparable modernization solutions within the past five years.
At least one of those workflow solutions must have been personally developed or materially enhanced within the past three years.
At least three years of recent experience personally developing BI products, dashboards, metrics, visualizations, analytical products, or comparable decision-support solutions.
At least one personally developed decision-support product must have been used operationally by an identified program, portfolio, management, or operational user group.
Demonstrated hands-on experience applying data modeling, data quality, or data-governance practices to an operational data or analytical solution.
Practical experience in at least two of the following: data models/relationships, metadata/common data standards, validation/data-quality controls, or lineage/stewardship/authoritative-source controls.
Experience documenting and transferring at least one data, analytical, or digital solution for continued operation by another developer, support team, platform owner, or operational organization.
Recent experience using Git or equivalent source control, versioned platform deployment, or a documented configuration baseline under change control.
At least two years of recent experience working directly with users or decision-makers to elicit requirements and communicate analytical findings, limitations, risks, or decision implications.

Nice To Haves

Experience supporting NATO, DoD, or another defense or multinational organization.
Experience developing data solutions for program, portfolio, infrastructure, capability-development, or acquisition environments.
Advanced proficiency with SQL and Python or another qualifying analytical programming language.
Experience with Power BI, Tableau, or comparable BI and visualization platforms.
Experience with ETL/ELT tooling, APIs, relational databases, and enterprise data services.
Experience designing low-code/no-code workflows or digital data-collection applications.
Familiarity with data governance, metadata, data lineage, stewardship, and authoritative-source management.
Experience using Git or comparable source-control tools in a collaborative technical environment.
Experience transitioning prototypes or pilot solutions into sustained operational environments.
Experience presenting data-driven findings to senior program, portfolio, military, or government leadership.

Responsibilities

Deliver hands-on data integration, data engineering, analytics, and decision-support solutions for NATO’s Enabling Capabilities Portfolio.
Work directly with users and stakeholders to identify priority decisions, information requirements, data sources, data gaps, and modernization opportunities.
Design, develop, test, and maintain repeatable processes for ingesting, transforming, reconciling, and preparing data from multiple enterprise sources.
Develop structured data models, common definitions, reference data, business rules, and data-quality controls.
Design and improve digital data-collection applications and workflows that reduce manual, spreadsheet-heavy, and email-driven business processes.
Support continued development and operational use of digital Management and Oversight Review data-collection and decision-support solutions.
Develop dashboards, metrics, visualizations, analytical products, and related decision-support tools.
Apply descriptive and diagnostic analytics and, when appropriate, predictive or prescriptive methods to identify trends, anomalies, risks, dependencies, and opportunities.
Integrate data using relational databases, APIs, data services, structured exchanges, ETL/ELT processes, and comparable interfaces.
Identify and address data-quality, lineage, ownership, governance, stewardship, and authoritative-source issues.
Apply sound development practices, including source control, configuration management, reproducible processing, documented transformations, and controlled deployment.
Document data sources, models, transformations, business rules, analytical logic, assumptions, dependencies, and operating procedures.
Conduct user testing and iteratively improve solutions based on operational use, data-quality findings, and stakeholder feedback.
Assess whether delivered solutions improve data quality, timeliness, workflow efficiency, information availability, and usefulness to decision-makers.
Present analytical findings, assumptions, limitations, risks, and decision implications to program managers and portfolio leadership.
Support transition of successful prototypes, pilots, data products, and analytical solutions to enduring production or enterprise environments.