Data Modeler (Secret Cleared)

CGI•Arlington, VA

1d•Onsite

About The Position

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.

Requirements

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).

Nice To Haves

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).

Responsibilities

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.