Database Administrator III

TX-HHSC-DSHS-DFPS•Austin, TX

10d•$7,350 - $7,653•Hybrid

About The Position

Database Administrator (DBA) III reports to the Data Management (DM) Unit director and performs highly complex (senior-level) data research, analysis, and database administration functions for the Data Management team within Information and Data Management, Office of Data, Analytics, and Performance (DAP). The DBA III supports various DAP administered data assets, including Snowflake, SQL Server, and Oracle systems, and is responsible for managing and leading the design, development, operational management, and optimization of data infrastructure. This role supports core business functions such as data engineering, data integration, database and query performance optimization, data analytics support, database security, backup and recovery, and compliance with data governance policies. Works under limited supervision, with considerable latitude for initiative and independent judgment.

Requirements

Knowledge of the various Texas Health and Human Services (HHS), with special focus on Medicaid and CHIP, including state and federal laws, rules, funding, eligibility requirements, services, policies, procedures and operations.
Knowledge of data engineering principles, database administration, data architecture, ETL/ELT processes, data integration, and data lifecycle management in enterprise data environments.
Knowledge of relational and cloud-based database technologies, including SQL Server, Oracle, Snowflake, and similar platforms used to store, integrate, and manage large and complex datasets.
Knowledge of ETL and data integration technologies, including Informatica PowerCenter/IICS, SSIS, APIs, scripting, and automated workflows used to extract, transform, validate, and load data.
Knowledge of data warehousing, data marts, dimensional modeling, database structures, data pipelines, metadata, data lineage, and source-to-target mapping concepts.
Knowledge of data quality management principles, including data profiling, validation, reconciliation, exception handling, root-cause analysis, and implementation of data quality controls.
Knowledge of data analytics and business intelligence concepts, including preparation of analysis-ready datasets, development of data models, reporting, dashboards, metrics, and performance indicators.
Knowledge of data visualization principles and tools, such as Tableau, Power BI, SAS, or comparable technologies used to communicate trends, patterns, performance measures, and analytical findings.
Knowledge of data governance, security, privacy, access controls, documentation, retention, and regulatory requirements applicable to enterprise and health and human services data environments.
Knowledge of the principles, practices and techniques of database design and development, database structures and theories, and current database technologies.
Knowledge of data engineering and data integration principles and practices.
Knowledge of SQL scripting, query optimization, and data modeling.
Knowledge of database performance optimization.
Knowledge of data storage, architecture, maintenance, and monitoring.
Strong analytical and problem-solving skills.
Effective communication and collaborations skills.
Knowledge of cost estimating techniques, data testing techniques, and project control.
Skills in the use of desktop computers running Windows OS and MS Office.
Skills in the use of database management systems, such as MS SQL Server, Oracle, and Snowflake.
Skill in designing, developing, maintaining, troubleshooting, and optimizing ETL/ELT pipelines and automated data workflows that integrate data from multiple systems and platforms.
Skill in using SQL and database management tools to query, transform, analyze, validate, reconcile, and troubleshoot large and complex datasets.
Skill in using ETL, cloud, database, and automation technologies to support modernization, migration, integration, and ongoing operation of enterprise data assets.
Skill in data engineering, including developing reusable data pipelines, transforming source data into standardized structures, implementing business rules, and preparing reliable datasets for reporting and analytics.
Skill in data analysis and data profiling to identify trends, anomalies, missing data, inconsistencies, performance issues, and opportunities for improving data quality.
Skill in supporting the development of dashboards, reports, visualizations, analytical datasets, and performance measures that enable program and leadership decision-making.
Skill in database performance monitoring and optimization, including query tuning, indexing, workload analysis, capacity considerations, and troubleshooting database and pipeline performance.
Skill in developing and maintaining technical documentation, including data dictionaries, source-to-target mappings, data lineage, workflow diagrams, operating procedures, technical specifications, and troubleshooting guides.
Skill in problem solving and root-cause analysis for complex database, ETL, data quality, and integration issues.
Skill in communicating technical information clearly to technical and non-technical stakeholders and collaborating with analysts, program staff, data governance teams, IT teams, vendors, and leadership. Skill in complex problem solving and critical thinking, and in the use of a computer and applicable software.
Skills in using ETL software and data integration tools, such as informatica PowerCenter/IICS, SSIS, Snowflake, and related technologies, to develop, maintain, troubleshoot, and optimize automated data workflows.
Skills in performing data extraction, transformation, validation, and loading data into the data assets.
Skills in integrating data across multiple platforms, and support reliable, accurate, and timely data processing.
Ability to support the Data Management Unit's objectives of providing reliable, accurate, secure, timely, and accessible data for operational, analytical, reporting, and decision-making needs.
Ability to independently design and implement scalable data engineering solutions that improve automation, reduce manual processing, strengthen data quality, and increase the reliability of enterprise data pipelines.
Ability to manage and support complex data environments involving multiple databases, source systems, cloud platforms, ETL technologies, and downstream analytical applications.
Ability to translate business and analytical requirements into technical data solutions, including database structures, transformations, workflows, data models, and analysis-ready datasets.
Ability to collaborate with data analysts and business teams to prepare, validate, and optimize data for analytics, reporting, visualization, performance measurement, and executive decision support.
Ability to identify opportunities to automate recurring data processes, modernize legacy workflows, improve performance, and reduce duplication of data and processing activities.
Ability to assess data quality issues, determine root causes, coordinate corrective actions, and establish preventive controls and monitoring processes.
Ability to support data migration and modernization initiatives, including migration of legacy databases and ETL processes to cloud-based data platforms while maintaining data integrity and business continuity.
Ability to balance multiple priorities and respond effectively to production issues, data requests, modernization projects, compliance requirements, and operational deadlines.
Ability to work collaboratively across organizational boundaries and contribute to the unit's broader goals for data engineering, analytics enablement, data governance, documentation, standardization, automation, and continuous improvement.
Ability to identify and define users’ functional and technical database needs, to conduct short-range and long-range project planning studies, to develop reports, and to communicate effectively.
Ability to develop technical documentation and standard operating procedures.
Ability to gather, assemble, correlate and analyze facts and data.
Ability to devise solutions to problems.
Ability to prepare concise and detailed reports.
Ability to develop and evaluate policies and procedures.
Ability to work independently and to meet deadlines.
Ability to oversee and/or supervise the work of others.
Database Administration Experience.
Experience with SQL and Database Development.
ETL and Data Integration Experience.
Experience with Data Engineering and Cloud Technologies.
Database Performance and Troubleshooting Experience.
Data Quality and Validation Experience.
Experience with Database or Data Management Automation/Scripting.
Analytics and Reporting Support Experience.
Experience with Documentation and Knowledge Transfer.

Nice To Haves

Graduation from an accredited four-year college or university. Major coursework in computer science, computer information systems, data engineering, data science, database management systems or related field, database/cloud certifications, or demonstrated advanced technical training is preferred. Experience may be substituted for education on a year for year basis.

Responsibilities

Develops, maintains, and enhances Extract, Transform, and Load (ETL) processes for data ingestion and integration. Ensures seamless data flows between operational and analytical systems. Troubleshoots ETL issues and optimizes processes for efficiency. Supports the implementation of data governance frameworks and best practices. Maintains accurate metadata and data lineage documentation. Collaborates with the DM team and external vendors to develop and integrate new data sources and pipelines. Reviews and approves technical designs provided by vendors to ensure alignment with architectural and data governance standards. Supports migrations to new data management system software levels and tests the migrations to ensure data reliability and functionality.
Monitors and fine-tunes database performance, including query optimization and indexing. Analyzes system performance metrics and recommends improvements. Works with developers to optimize SQL queries and database design. Defines, develops, and implements data and reporting standards. Monitors system health and database performance proactively and works with IT and its vendors to apply patches and updates to database software as needed.
Implements and maintains data validation, cleansing, and standardization techniques to improve data quality. Collaborates with data owners to enforce data integrity constraints. Identifies and addresses inconsistencies, anomalies, and redundancies in datasets. Supports the development and maintenance of enterprise data warehouse and data mart solutions Recommends goals to improve database efficiency and cost-effectiveness. Aligns data processes with enterprise data governance policies, including metadata, lineage, and stewardship standards. Collaborates with data governance and business teams to improve data accuracy, cost-effectiveness, consistency, and completeness in database systems.
Manages database security, including user roles, permissions, and authentication controls. Conducts periodic security audits and implements access policies. Ensures compliance with HHSC security standards and data protection regulations. Develops and maintains database backup and disaster recovery strategies. Performs routine backup and restoration tests to validate data integrity. Ensures minimal data loss and downtime in the event of a system failure.
Provides database and analytical support for reporting and business intelligence tools. Optimizes data structures to enhance report performance. Maintains comprehensive technical documentation for database systems, ETL logic, data workflows, data architecture, configurations, processes, and procedures. Develops database documentation, procedures, technical instructions, guidelines, and training materials. Provides status updates on emerging database and analytical technologies and industry best practices.