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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Management Analyst - **Company:** Everforth Apex - **Location:** Oklahoma City, OK, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Geographic Information Systems, Application Programming Interfaces (APIs), BigQuery, Cloud Database, Cloud Storage, Information Systems, Data Architecture, Data Dictionary, Data Governance, Data Integrity, Extract Transform Load (ETL), Data Structures, Database Queries, Digital Assets, Data Flow Control, Interoperability, Python (Programming Language), Metadata, Performance Tuning, Power BI, Data Streaming, Tableau (Software), Technical Data Management Systems, Scripting, Google Cloud, Sql Optimization, Google Data Studio, Snowflake, Data Layers, HR Software, Information Technology, Google Bigquery, Data Management, Data Pipelines - **Published:** September 22, 2026 - **Apply:** https://www.dice.com/job-detail/c3b3e411-8270-4f3d-9196-cbe18d675caa ## About the Role Education: Bachelor's degree in data management, information systems, computer science, engineering technology, or a related field. Experience: 3+ years of experience in data governance, data management, or business intelligence. Technical Skills: * Hands-on experience with cloud data warehouses (e.g., Google BigQuery), including table design, views, and dataset management. * Experience building enterprise data models (facts/dimensions, semantic layers) and ELT/ETL workflows. * Experience with BI tools (Looker Studio, Power BI, Tableau), including performance optimization. * Experience documenting data assets, including source-to-target mappings, data dictionaries, and transformation logic. Preferred Background * Experience with Google Cloud Platform services (BigQuery, Cloud Storage, Dataflow, Composer). * Knowledge of Python or a similar scripting language for analysis, automation, and pipeline support. * Experience building governed analytics environments and reusable data models. * Looker Studio development experience, including design standards, blending, and parameter controls. * Experience implementing automated data quality monitoring, validation frameworks, and governance dashboards. Other Requirements * Must pass background checks. * This position is onsite or hybrid based on management direction. ## Description The Data Management Analyst supports engineering, operations, and administrative programs by ensuring the accuracy, standardization, and controlled use of enterprise data. This role applies advanced governance practices to improve data architecture, cross-system interoperability, and the reliability of regulatory reporting. The analyst builds and maintains technical BI datasets and dashboards sourced from complex data pipelines to support modeling and analytics., * Help establish data standards, definitions, and quality rules across programs. * Maintain metadata, data documentation, and governance records. * Monitor, document, and improve data quality within engineering, environmental, construction, ROW, project delivery, GIS, and HR systems. * Work with departments to address data issues and improve data entry practices. * Support system integrations and data flows by reviewing data structures. * Apply schema and API validation, lineage analysis, and integration standards to improve interoperability. * Build and maintain dashboards and reports for 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. Core Competencies * Advanced SQL for complex queries, performance optimization, validation, and large-scale transformations. * Strong understanding of data governance principles including ownership, stewardship, metadata, lineage, and quality frameworks. * Ability to translate business requirements into technical data solutions such as metrics, KPIs, models, and dashboards. * Clear communication skills for technical and non-technical stakeholders and effective documentation practices. * Skill in designing dimensional and semantic models (star/snowflake) and medallion layer principles (Bronze/Silver/Gold). * Ability to manage multiple priorities and deliver reliable artifacts for audits and regulatory reporting. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Making Data Warehouses fast. 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