Data Architect - Prince William County Public Schools

This position plays a pivotal role in leading the architecture, design, and implementation of our next generation data solutions. In this hands-on role, you will architect and engineer data pipelines, platforms, integrations, and products on modern cloud platforms, such as Snowflake, Databricks, and/or Azure. Collaborating closely with the data leadership team, you will shape the long-term vision, cloud adoption roadmaps, future-state analytical architecture, and data governance frameworks necessary for this transformation.

Develop and implement data strategies for cloud data platform, master data management, metadata management, analytics, and data integration.

Design future-state analytical architecture and cloud migration roadmap.

Lead platform evaluation and hands-on build-out of data infrastructure on cloud technologies.

Define and implement data integration, security, governance, and metadata retention strategies in collaboration within DIIT and other departments and schools.

Implement methodologies and reuse strategies to enhance quality while optimizing development.

Define metadata strategy and lineage tracking capabilities.

Drive initiatives to improve system reliability, availability, and performance.

Lead cloud adoption while ensuring continuity of existing analytical initiatives.

Continuously monitor post-implementation architecture health, performance, and scalability.

Maintain continuity of existing analytics and data engineering initiatives during transformation.

Improve architecture health, scalability, and efficiency as changes emerge.

Design and document the Logical Data Model and develop a Physical Data Model.

Create and execute Data Definition Language (DDL) statements for Data Warehousing and/or Data Lake objects.

Drive and build data model and architecture, implementing frameworks to ensure adherence to data architecture.

Understand the existing SQL/processes.

Provide deep expertise in databases, data modeling, data architecture, and operating systems.

Support end-to-end data asset lifecycle management activities.

Design robust, scalable, real-time data pipelines and data platform architecture.

Lead the review and design of new data products, maintaining product documentation.