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Decision Support Engineer Jobs (NOW HIRING)

Determines how decision support systems will provide information required to make effective ... Developand maintainmoderate- to extremely-complex computer programs using 4GL programming languages ...

Determines how decision support systems will provide information required to make effective ... Developand maintainmoderate- to extremely-complex computer programs using 4GL programming languages ...

Our breakthrough wearable technologies support medical decision making and encourage patient ... Create reusable toolkits and templates that enable algorithm developers and clinical scientists to ...

Our breakthrough wearable technologies support medical decision making and encourage patient ... Create reusable toolkits and templates that enable algorithm developers and clinical scientists to ...

Our breakthrough wearable technologies support medical decision making and encourage patient ... Create reusable toolkits and templates that enable algorithm developers and clinical scientists to ...

Determines how decision support systems will provide information required to make effective ... Develop and maintain moderate-to extremely-complex computer programs using 4GL programming ...

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Decision Support Engineer information

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How much do decision support engineer jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for decision support engineer in the United States is $39.87, according to ZipRecruiter salary data. Most workers in this role earn between $29.57 and $46.63 per hour, depending on experience, location, and employer.

What is a decision support engineer?

A Decision Support Engineer is a professional who designs, develops, and maintains systems that help organizations make data-driven decisions. They work with large datasets, analytical tools, and business intelligence platforms to provide actionable insights to management and stakeholders. Their role often includes integrating data from multiple sources, creating dashboards, and implementing algorithms that support strategic business decisions. Decision Support Engineers collaborate closely with IT, data science, and business units to ensure that decision-making processes are efficient, accurate, and aligned with organizational goals.

What are the key skills and qualifications needed to thrive as a decision support engineer?

To thrive as a Decision Support Engineer, you need a solid background in data analytics, systems engineering, and problem-solving, often supported by a degree in computer science, engineering, or a related field. Familiarity with business intelligence tools (such as Tableau or Power BI), database management systems, and programming languages like SQL and Python is typically required. Strong communication, analytical thinking, and collaboration skills help you translate complex data into actionable insights for stakeholders. These competencies are essential for effectively supporting organizational decision-making and driving data-driven strategies.

How does a decision support engineer typically collaborate with data scientists and business stakeholders?

Decision Support Engineers play a key role in bridging the gap between technical data teams and business decision-makers. They work closely with data scientists to interpret complex models and ensure that data-driven insights are clearly communicated and actionable. Additionally, they engage with business stakeholders to understand their needs, translate them into technical requirements, and develop user-friendly tools or dashboards that support strategic decisions. This collaborative environment requires strong communication skills, adaptability, and a solid understanding of both technical and business perspectives.

What is the difference between Decision Support Engineer vs Data Analyst?

AspectDecision Support EngineerData Analyst
Required CredentialsBachelor's in Engineering, Computer Science, or related field; knowledge of data systemsBachelor's in Statistics, Mathematics, or related field; proficiency in data analysis tools
Work EnvironmentTechnical teams, engineering projects, data systemsBusiness units, reporting, data visualization
Industry UsageManufacturing, logistics, technologyFinance, marketing, healthcare
Common Search/ComparisonDecision Support Engineer vs Data Analyst

The Decision Support Engineer focuses on developing systems and tools to aid decision-making processes, often working with engineering and technical teams. In contrast, Data Analysts primarily interpret data to generate reports and insights for business decisions. While both roles require data skills, Decision Support Engineers typically have a stronger technical background in systems and engineering, whereas Data Analysts focus more on data interpretation and visualization.

What are popular job titles related to Decision Support Engineer jobs?

For Decision Support Engineer jobs, the most frequently searched job titles are:

Infographic showing various Decision Support Engineer job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 74% Full Time, 20% Part Time, and 5% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $82,930 per year, or $39.9 per hour.

Senior Data Integration & Decision Support Engineer

Norfolk, VA • On-site

Full-time

Medical, Dental, Retirement, PTO

Posted yesterday

New


Job description

Senior Data Integration & Decision Support Engineer
Location: Norfolk, Virginia
Work Arrangement: Full-time, on-site
Clearance: ACTIVE SECRET CLEARANCE FROM U.S. OR NATO MEMBER NATION REQUIRED
The Opportunity
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.
Key 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.
Required Qualifications
  • 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.
Preferred Qualifications
  • 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.

Clearance
This position requires an active National SECRET (or higher) security clearance from the U.S. or a NATO member nation. Applicants who do not possess the clearance specified above cannot be considered at this time.
Compensation
Compensation for this position ranges from $120,000 - $140,000 annually. Final salary will be based on factors such as experience, education, skills, qualifications, location, contract requirements, and overall affordability.
Eligible full-time employees may also receive a comprehensive benefits package, including medical and dental insurance, retirement benefits, paid leave, and professional development opportunities.
How to Apply
Email your resume to jobs@idw.inc with the subject line: “Senior Data Integration & Decision Support Engineer – (Your Name) Application” or respond to this job posting via the included web application.
Ironclad Defense Works is an Equal Opportunity Employer.
 

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