Data Management and Analytics Engineer

Position Summary

MAG is staffing for a Data Management and Analytics Engineer to transform raw data into strategic intelligence through advanced analytics and data engineering. You'll architect scalable data solutions using the SAS platform, enabling data-driven decision making that directly supports mission-critical operations and business objectives.

Primary Responsibilities

• Design and implement robust data pipelines using SAS Viya and SAS Data Integration Studio
• Lead migration initiatives from legacy data environments to SAS Viya cloud instances, including comprehensive data rationalization and modernization of existing algorithms for cloud-native computing architectures
• Develop advanced SAS programming solutions (Base SAS, SAS/STAT, SAS Macros, SAS/SQL) for complex data transformations
• Build statistical models and machine learning algorithms using SAS Enterprise Miner and SAS Visual Analytics
• Create automated ETL processes to extract, cleanse, and transform large datasets from diverse sources
• Implement data quality frameworks and governance standards to ensure accuracy and integrity
• Develop interactive dashboards and visualizations using SAS Visual Analytics and other BI tools
• Optimize data warehouse architecture and implement efficient data modeling principles

Secondary Responsibilities

• Create comprehensive reports and presentations to communicate analytical findings to stakeholders
• Collaborate with business analysts and data scientists to translate requirements into technical solutions
• Maintain and enhance existing SAS code libraries for efficiency and reusability
• Provide technical mentoring and knowledge transfer to junior team members
• Support data governance initiatives and compliance with industry regulations
• Implement data security protocols and access controls within SAS environments
• Document analytical processes and maintain comprehensive technical specifications

Requirements

• 5+ years of hands-on experience in data management, data engineering, or analytics
• Extensive, proven experience with SAS Viya platform including SAS Enterprise Guide and SAS Data Integration Studio
• Expert-level SAS programming skills with focus on data manipulation, ETL processes, and statistical analysis
• Strong proficiency in SQL for querying and manipulating relational databases (Oracle, SQL Server, PostgreSQL)
• Experience with data warehousing concepts, dimensional modeling, and database optimization
• Strong scripting skills (Python, R, or advanced SAS macro programming)
• Understanding of statistical analysis, data mining, and machine learning techniques
• Experience with cloud platforms (Azure required, AWS/GCP beneficial)
• Knowledge of data visualization tools (SAS Visual Analytics, Tableau, Power BI)

Education

• Bachelor's degree in Computer Science, Statistics, Mathematics, or related quantitative field
• Preferred – Master's degree in Statistics, Data Science, or related analytical field

Clearance

• Must be eligible for Secret security clearance
• US Citizenship required

Special Note

What Makes You Successful Here

• You turn complex datasets into actionable insights
• You build scalable, maintainable data solutions, not one-off analyses
• You implement data quality into pipelines, not validate it after the fact
• You can work across on-premises, cloud, and hybrid data environments
• You measure success by the business impact of your analytical solutions

• SAS Global Certifications (Base Programming, Advanced Programming, Data Integration)
• Experience with SAS Visual Analytics and SAS Enterprise Miner
• Knowledge of machine learning frameworks and advanced statistical modeling
• Familiarity with big data technologies (Hadoop, Spark, NoSQL databases)
• Experience with version control systems (Git) and collaborative development practices
• Understanding of data privacy regulations and compliance frameworks
• Experience with the Department of Defense or similarly regulated environment.

Former US Defense Contractor / US Gov / US Military Experiences Only

This is a Hybrid Position – Remote mainly - but as well on call to come into a MAG office when requested.

We are seeking candidates who live in proximity to our corporate HQ in Fairfax, VA primarily but will entertain persons living near our satellite offices in:

Aberdeen, MD – Titusville, FL - Newport News, VA - Carthage NC

At MAG Aerospace, we value your contributions providing our employees with a robust Total Rewards package that supports your total well-being. Full-time and part-time employees working at least 30 hours a week on a regular basis are eligible to participate in MAG's Total Rewards programs. Our offerings include health, life, disability, financial, and retirement benefits as well as paid leave, professional development, and tuition assistance.

Individuals that do not meet the threshold are only eligible for select offerings not inclusive of health benefits. We encourage you to learn more about our Total Rewards Program by visiting the Resource page on our Careers site: https://www.magaero.com/benefits/. Salary at MAG Aerospace is determined by various factors including but not limited to location, the particular combination of education, knowledge, skills, competencies, and experience as well as contract-specific affordability and organizational requirements.

The projected compensation range for this position is $80500 to $149500 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of MAG's total compensation package for employees.

• Work on meaningful analytics problems that directly impact national security
• Small, elite team where your data insights drive immediate operational decisions
• Access to cutting-edge SAS technologies and large-scale datasets
• Rapid analytics environment – see your models deployed and making impact quickly
• Direct interaction with stakeholders and end users of analytical products
• Professional development including SAS certification and conference attendance support
• Flexible work arrangements with occasional field exercises and customer site visits
• Opportunity to shape the future of mission-critical data analytics and intelligence