Job Summary
The Data Management Analyst supports engineering, operations, and administrative programs by ensuring the accuracy, standardization, governance, and controlled use of enterprise data. The role applies data governance practices to improve data architecture, cross-system interoperability, data quality, and regulatory reporting. The analyst will build and maintain technical BI datasets, dashboards, data models, and reporting solutions sourced from complex data pipelines to support analytics, forecasting, and operational decision-making.
Key Responsibilities
Establish and maintain data standards, definitions, and quality rules across programs.
Maintain metadata, data documentation, and data governance records.
Monitor, document, and improve data quality across engineering, environmental, construction, ROW, project delivery, GIS, and HR systems.
Collaborate with departments to address data quality issues and improve data entry practices.
Support system integrations and data flows by reviewing data structures and integration requirements.
Apply schema and API validation, data lineage analysis, and integration standards to improve cross-system interoperability.
Build and maintain dashboards and reports supporting program performance, regulatory reporting, and operational insights.
Develop technical BI datasets sourced from complex data pipelines to support analytics and forecasting.
Collaborate on statewide data governance initiatives, standards, and policies.
Partner with data engineers, analysts, business users, and data owners to improve data reliability, accessibility, and usability.
Develop complex SQL queries and transformations for data validation, analysis, and performance optimization.
Translate business requirements into technical data solutions, including metrics, KPIs, data models, and dashboards.
Design and maintain dimensional and semantic models using star and snowflake schemas and medallion-layer principles.
Manage and deliver reliable data artifacts supporting audits and regulatory reporting.
Required Qualifications
Bachelor's degree in Data Management, Information Systems, Computer Science, Engineering Technology, or a related field.
3+ years of experience in data governance, data management, or business intelligence.
Advanced SQL skills, including complex queries, performance optimization, data validation, and large-scale transformations.
Hands-on experience with cloud data warehouses such as Google BigQuery, including table design, views, and dataset management.
Experience building enterprise data models, including facts, dimensions, and semantic layers.
Experience developing and supporting ELT/ETL workflows.
Experience with BI tools such as Looker Studio, Power BI, or Tableau, including performance optimization.
Experience documenting data assets, including source-to-target mappings, data dictionaries, and transformation logic.
Strong understanding of data governance principles, including data ownership, stewardship, metadata, lineage, and data quality frameworks.
Experience with data quality management and validation practices.
Strong understanding of dimensional and semantic modeling, including star and snowflake schemas and Bronze/Silver/Gold medallion-layer principles.
Strong communication and documentation skills, with the ability to work effectively with technical and non-technical stakeholders.
Ability to manage multiple priorities and deliver reliable data artifacts for audits and regulatory reporting.
Ability to pass applicable background checks.
Preferred Qualifications
Experience with Google Cloud Platform services, including BigQuery, Cloud Storage, Dataflow, and Composer.
Knowledge of Python or a similar scripting language for analysis, automation, and data pipeline support.
Experience building governed analytics environments and reusable data models.
Experience developing Looker Studio solutions, including design standards, data blending, and parameter controls.
Experience implementing automated data quality monitoring, validation frameworks, and governance dashboards.
Experience supporting enterprise data governance initiatives and cross-system data integration.