Data Modeler; Secret Cleared

Data Modeler (Secret Cleared)

Category: Analytics and Emerging Digital Technologies

Main location: United States, Virginia, Arlington

Position : J

Employment Type: Full Time

CGI Federal is seeking a Data Modeler to design and maintain curated (Gold) data models within an Azure Data Lake/Databricks environment to enable consistent reporting and analytics. This role requires an active Secret security clearance and will focus on Gold model development, IVV model certification support, and resolving end user feedback to improve data usability, consistency, and integrity.

This position is located in Arlington, VA.

• Design, develop, and maintain Gold layer data models in an Azure Data Lake/Databricks environment to support analytics and reporting use cases.
• Partner with stakeholders to elicit and document data requirements, business definitions, and modeling assumptions.
• Define entities, relationships, and dimensional structures; maintain data dictionaries, model diagrams, and related documentation.
• Collaborate with data engineering teams to ensure model implementation aligns with design standards, naming conventions, and refresh expectations.
• Support IVV activities for model certification, including evidence collection, walkthroughs, traceability to requirements, and remediation of findings.
• Validate model outputs through reconciliation, completeness checks, and data quality reviews (e.g., SQL based validation and Databricks notebooks as appropriate).
• Triage and resolve end user feedback related to model logic, definitions, and usability; document decisions and changes.

• Bachelor's degree in Information Systems, Computer Science, Data/Analytics, Engineering, or related field.
• 1–4 years of experience in data modeling, data analysis, or data management.
• Experience building logical and physical data models (dimensional and/or relational).
• Proficiency in SQL for data validation and troubleshooting.
• Experience documenting business definitions, lineage, and model rules.
• Experience supporting testing/validation activities and addressing defects/findings.
• Strong written/verbal communication skills for working with technical teams and business users.
• Active Secret security clearance (required).

• Experience with Databricks (e.g., notebooks, Spark concepts, Delta Lake).
• Experience with Azure data services commonly used in lake/lakehouse architectures (e.g., ADLS, Azure Data Factory, Azure Synapse).
• Familiarity with medallion/lakehouse concepts (Bronze/Silver/Gold) and data warehousing principles.
• Experience with modeling tools (e.g., ER/Studio, ERwin, Visio, or similar).
• Experience supporting IVV or audit style certification processes.
• Familiarity with Agile delivery (user stories, acceptance criteria, backlog refinement).

• Competitive compensation
• Comprehensive insurance options
• Matching contributions through the 401(k) plan and the share purchase plan
• Paid time off for vacation, holidays, and sick time
• Paid parental leave
• Learning opportunities and tuition assistance
• Wellness and Well being programs

• Azure Data Lake
• Data Analysis
• Data Modeling
• SQL
• Databricks

Compensation range (U.S.): $51,600.00 – $

Qualified applicants will receive consideration for employment without regard to their race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation or perceived sexual orientation, gender, gender identity, and gender expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, height, weight, or any other legally protected status or characteristics to the extent required by applicable federal, state, and/or local laws where we do business.

CGI provides reasonable accommodations to qualified individuals with disabilities. If you need an accommodation to apply for a job in the U.S., please email the CGI U.S. Employment Compliance mailbox at US_ . You will need to reference the Position  the position in which you are interested.