Data Architect

Data Architect C. Advanced (RFQ)

Location: Tallahassee, FL 32399

Type: 6-month contract

As part of the Department's ongoing efforts to modernize core enterprise data systems, various data initiatives for the strategic priorities of safety, mobility, cybersecurity, and operational efficiency must be documented and modernized for implementation of a framework to enable scalable data integration and analytics.

The successful candidate will design and implement a data integration framework to support enterprise data. The enterprise data assets consist of interfaces, enterprise applications, databases, automated processes, and reporting programs within the Department. The candidate will guide the transition and integration of the enterprise data to unify various asset domains. The integration framework is anchored on three complementary components.

• Join location data with engineering datasets

• Integration backbone—orchestrate extract transform and load (ETL) pipelines, application programming interface (APIs), and service endpoints. Provides interoperable data flows across statewide enterprise systems and enforces lineage, stewardship, and “collect once, use many” principles.

• Blueprint to standardize data schemas.

Together, these components transform the Department’s enterprise data ecosystem into a connected, governed, and analytics ready environment. Each data asset shares a common foundation of enterprise technology and governance. This involves reviewing as-is business processes, remediation strategies, reengineering, design, and integration. Ensuring compatibility with cloud architecture is a key objective, aligning with the state’s cloud-first policy. The role focuses on the analysis and remediation of data that is secure and scalable and built upon the foundation of platforms the Department has already invested in such as Azure, Snowflake, Informatica, and PostgreSQL. Once the data is integrated and provisioned within the agency the candidate will then verify data quality.

Scope:

1. Current State Assessment:

• Review existing systems to identify any data silos, schema inconsistencies and governance gaps.

• Engage stakeholders to gather and document their integration needs Analyze and verify existing data models to assess impacts related to implementation of a modern data model.

• Evaluate the existing data models for dependencies and assess the scope of necessary changes.

• Conduct impact analysis on reporting and application usage of data models to ensure business outcomes are not disrupted.

2. Framework Design and Architecture:

• Define the enterprise data architecture strategy, including canonical models, application programming interfaces (APIs), and ontologies.

• Map integration points across AZURE, Snowflake, Informatica, and PostgreSQL.

• Develop conceptual, logical, and physical data models for key domains (e.g. financial, roadway characteristic, and work program administration).

• Provide a comprehensive re-design of data models for various enterprise domains.

• Ensure that the redesigned canonical data models are scalable, robust, and aligned with best practices in data management, supporting both current and future business needs.

• Ensure spatial data integration with GIS systems.

3. Data Governance and Quality:

• Implement established governance structure, meta data standards, and stewardship roles.

• Design and implement data quality measures to ensure the timeliness, accuracy, and completeness of production data on a scheduled basis, including nightly, hourly, or less frequent intervals as needed.

• Collaborate with development teams to automate and streamline ETL processes to support efficient data flow and integration.

• Create metadata standards, lineage tracking, and stewardship roles that compliment existing roles defined in Informatica and Snowflake.

4. Data Integration and Interoperability:

• Build ETL/ELT pipelines and real-time streaming solutions with a unified structure for ingestion and exchange for enterprise datasets

• Ensure consistent identifiers enterprise Application.

• Enable data exchange across internal systems and with external systems

• Implement Orchestration using Informatica/AZURE Data Factory or Snowflake.

• Design RESTful endpoints for spatial and engineering data.

5. Technical Leadership and Strategic Support:

• Collaborate with Transportation Technology leaders to develop tactical strategies for the planning, design, implementation, and maintenance of enterprise data integration initiatives.

• Provide guidance on high-level design choices and technical standards, including software coding standards, tools, and platforms.

• Act as an internal consultant, mentor, and advocate to team members, support ongoing improvements, and change management initiatives across the Department’s computing assets.