Data Engineer

KeyLogic Systems; United States; Remote; USD 140,000 - 170,000; Full time

Benefits offered by this job

Health insurance

Job summary

KeyLogic Systems is seeking a Data Engineer to support the Office of the Department of the Air Force (DAF) Chief Data and AI Officer. The role focuses on collecting, integrating, validating, and analyzing enterprise data to measure maturity and inform senior leaders.

The position involves building data pipelines, dashboards, and automated scoring to provide visibility into performance and progress across enterprise platforms, in a remote work setting.

Qualifications

• Seven+ years of data engineering or data integration experience.
• Experience designing enterprise-scale data pipelines and ETL/ELT processes.
• Experience with data visualization, dashboards, and reporting solutions.

Responsibilities

• Collect, integrate, validate, and analyze data from multiple sources.
• Develop dashboards, scorecards, and analytics products for leadership insight.
• Support design, implementation, and improvement of assessment and reporting capabilities.

Skills

Data engineering

ETL/ELT

Data visualization

Data pipelines

AWS cloud

SQL

Analytical problem solving

Education

Bachelor’s degree in computer science or related field

Master’s degree preferred

Tools

Palantir Foundry

Databricks

Power Platform

Power Apps

Data mesh concepts

Job description

Job Title: Data Engineer

Location: Remote

Clearance: DOD Secret Clearance Required

Salary: $140-170k + Comprehensive Benefits Package

KeyLogic is seeking a Data Engineer to support the Office of the Department of the Air Force (DAF) Chief Data and AI Officer (CDAO) in measuring and advancing enterprise data and SI maturity across the Department. The Data Engineer will serve as a key contributor to the collection, integration, validation, analysis, and visualization of assessment data used to evaluate organizational capabilities, track progress toward strategic objectives, and inform senior leader decision-making.

Working across enterprise platforms and mission stakeholders, the Data Engineer will support data pipelines, scoring methodologies, dashboards, reports, and analytics that provide visibility into enterprise performance and maturity outcomes. The role supports the integration of assessment activities into the DAF Data Mesh Environment (DME) and related platforms while enabling scalable, repeatable, and data-driven assessment processes.

The successful candidate will combine strong data engineering expertise with analytical problem-solving skills to deliver trusted data products, enterprise reporting capabilities, and innovative solutions that support DAF data, SI, and digital transformation initiatives.

What You’ll Deliver

• Trusted data and analytics supporting enterprise decision-making.
• Automated scoring, reporting, and visualization capabilities.
• Dashboards, metrics, and maturity-assessment insights for leadership and stakeholders.
• Integrated assessment solutions within DAF Data Platforms.
• Validated enterprise reporting products and performance measures.
• Actionable recommendations derived from assessment results and analytics.
• Innovative prototypes and automation solutions that improve enterprise assessment and reporting processes.
• Capabilities, and solutions that transform the DAF Data & SI Strategies from intent into measurable outcomes by enabling enterprise visibility, maturity improvement, data-driven decision-making, and sustained mission impact.

What You’ll Do

• Collect, integrate, validate, and analyze data from enterprise platforms, mission systems, surveys, inventories, and other designated data sources.
• Support the design, implementation, and continuous improvement of assessment, scoring, reporting, and visualization capabilities.
• Transform disparate and complex data sources into trusted data products that support enterprise reporting, performance measurement, and decision-making.
• Develop dashboards, scorecards, metrics, and analytics products that provide visibility into organizational maturity, capability adoption, performance trends, and strategic outcomes.
• Collaborate with government stakeholders, assessment teams, platform owners, and functional organizations to establish data requirements, business rules, scoring methodologies, and reporting needs.
• Evaluate data quality, completeness, accuracy, and consistency across assessment data sources and implement processes to improve data integrity.
• Develop data models, analytical datasets, and reporting structures that enable enterprise-wide assessment and maturity analysis.
• Create executive-level visualizations and reporting products that communicate assessment results, performance insights, risks, trends, and opportunities for improvement.
• Support development and refinement of enterprise metrics, key performance indicators, and maturity measurement frameworks used to assess progress toward Data and SI strategic objectives.
• Implement best practices for data engineering, analytics, documentation, and automation using Agile and DevSecOps methodologies.
• Document data flows, transformation logic, scoring methods, integration patterns, and standard operating procedures to ensure transparency, repeatability, and long-term sustainment.
• Build and maintain low-code enterprise solutions that streamline assessment administration, workflow management, information collection, and reporting activities.
• Support prototype, pilot, and proof-of-concept initiatives that explore innovative approaches to data collection, assessment automation, analytics, and enterprise reporting.
• Develop and execute test scenarios, validation procedures, and user acceptance testing activities for data platforms/integrations, pipelines, reporting solutions, and enterprise data products.
• Partner with data scientists, architects, engineers, and mission stakeholders to advance data-driven decision-making and continuous improvement across the Department of the Air Force.
• Provide technical expertise on enterprise data, analytics, and assessment practices while helping expand adoption of data-driven performance measurement and decision support capabilities.

Required Education

Candidates must meet one of the following combinations:

• Bachelor’s degree in computer science, information systems, engineering, data science, or a related technical field; equivalent directly relevant experience may be considered
• Master’s degree preferred

Required Qualifications

• Secret Clearance
• Minimum of seven (7) years of experience in data engineering, data integration, or related data-focused disciplines.
• At least three (3) years of experience supporting data analytics environments, preferably within the Department of War, Intelligence Community, or other Federal organizations.
• Experience designing, developing, and maintaining enterprise-scale data pipelines and ETL/ELT processes.
• Experience collecting, integrating, cleansing, validating, and managing large structured and unstructured datasets.
• Experience developing data visualizations, dashboards, and reporting solutions.
• Familiarity with cloud-based data platforms and services, particularly AWS environments.
• Experience with SQL and modern database technologies, including relational and analytical data platforms.
• Experience supporting API integrations and data exchange mechanisms.
• Knowledge of modern data architecture concepts including data lakes, data fabrics, data mesh, metadata management, and data governance.
• Understanding of Agile delivery methodologies and DevSecOps practices.
• Strong written and verbal communication skills with the ability to collaborate across technical and non-technical stakeholders.

Preferred Qualifications

• Top Secret Clearance
• Experience with DoW/DAF data ecosystems and mission systems
• Microsoft Power Apps and Power Platform experience strongly preferred.
• Experience developing and applying DoDAF architecture views
• Palantir Foundry experience
• Familiarity with machine learning data pipelines and MLOps concepts.
• Databricks experience a plus.
• Relevant cloud, data engineering, or data analytics certifications a plus.