Senior Data Solution Engineer

DHS Suitability Required

About Aretum Aretum is a mission-driven organization committed to delivering innovative, technology-enabled solutions to our customers across defense, civilian, and homeland security sectors. Our teams work at the intersection of strategy, technology, and transformation, helping agencies solve their most critical challenges. We believe in investing in our people and creating a culture where collaboration, inclusion, and professional growth are at the forefront.

Job Summary Aretum is seeking a Senior Data Solution Engineer that will focus on designing data governance, tagging, and metadata standards and working with medallion architecture. The Senior Data Solution Engineer will support consequential design decisions and assist with determining whether solutions scale or accumulate technical debt.

Due to the nature of our work as a federal consulting organization, employees may be expected to handle Controlled Unclassified Information (CUI) and must adhere to applicable safeguarding and compliance requirements.

Responsibilities Design and implement data management and governance solutions within Databricks and Unity Catalog, ensuring data sets are properly classified, documented, secured, and managed throughout their life cycle. Support data architecture and design decisions by evaluating solution scalability, maintainability, and performance. Develop and implement data governance tagging, meta standards, and classification frameworks to support data discovery, traceability, compliance, and consistent governance practices. Define and enforce governance requirements across Bronze, Silver, and Gold layers of the medallion architecture, ensuring metadata, data sensitivity classifications, and access controls evolve appropriately as data is transformed and refined. Implement and maintain column level masking, row level security, and dynamic access controls to protect sensitive data while enabling authorized access for appropriate users and business purposes. Develop and optimize data pipelines using SQL and Spark, ensuring reliable, scalable and efficient data processing in production environments. Collaborate with technical terms, data owners, security stakeholders and business partners to reconcile competing requirements and translate them into practical data solutions.