Data Engineer; SR

Job Summary The Senior Data Engineer designs, builds, and optimizes enterprise data solutions that enable data-driven decision-making and operational excellence across TMRS. This role is responsible for the architecture and implementation of data pipelines, data repositories, and reporting platforms; applies data engineering and data governance standards; and leads the integration and operationalization of artificial intelligence and machine learning capabilities. Working within the IS Department, this role partners closely with business stakeholders and Executive Leadership to deliver secure, scalable, reliable, and high-quality data solutions that support organizational objectives.

Key Responsibilities Design, develop, and maintain reports, dashboards, and business intelligence solutions aligned with organizational objectives.

Architect, build, and optimize scalable data pipelines and cloud-based data solutions using modern SaaS and PaaS platforms.

Design and maintain data models, including dimensional and semantic models, that make enterprise data usable and consistent across reporting and analytics.

Develop and tune complex queries and transformations using SQL, PL/SQL, T-SQL, and Python to support ETL and ELT processes.

Create and maintain reliable data repositories, ensuring accurate data lineage, documented definitions, and data integrity across on-premises and cloud environments.

Integrate data from systems of record using established data modeling standards

Establish automated data quality monitoring, reconciliation, and pipeline observability; define and report on data quality measures.

Lead enterprise AI and machine learning initiatives, including model integration and operationalization.

Establish and maintain end-to-end model lifecycle management processes, including version control, validation and approval, deployment standards, continuous performance monitoring for drift and accuracy, and scheduled periodic reviews with documented outcomes.

Enforce data governance standards, including data quality, data classification, retention, and access controls in alignment with organizational policies and Texas records retention requirements.

Ensure proper data usage controls for AI, including approved data sources, data privacy, and secure handling of sensitive member information.

Produce control evidence supporting internal audit, external examinations such as SOC, and NIST-aligned security control reviews.

Translate business needs and stakeholder requests into technical requirements, and lead technical projects from intake through design, development, and implementation.

Lead peer review of code, models, and reports.

Mentor mid-level and junior data staff and build analytics capability among business users.

Collaborate using Agile methodologies and tools such as JIRA, Confluence, and Git to support iterative development and delivery.

Investigate new technologies and assess their viability and usefulness in current and future projects.

Improve process, performance, and security of data solutions and integrations.

Contribute new viewpoints and strategies to stimulate growth.

Ability to use and integrate approved AI solutions.

After hours support as needed.

Other duties as assigned.

Follow all applicable policies and procedures including all security policies.

Education & Experience Hands-on experience with Advanced SQL (Oracle PL/SQL and T-SQL) and Python for data engineering, transformation, and analysis

Cloud data platforms and services (Azure and AWS), including storage, compute, and managed data servicesETL and ELT pipeline design, orchestration, and scheduling

Data warehouse, lakehouse, and dimensional modeling

Business intelligence and reporting platforms (Power BI or equivalent)
Data governance practice: classification, lineage, retention, and access control

Machine learning model integration and lifecycle management (MLOps)
Agile delivery tooling: JIRA, Confluence, and Git-based source control

Required

Bachelor’s degree in data science, computer science, information systems, engineering, actuarial science, mathematics, statistics, or related field and a minimum of 7 years of experience delivering data solutions, analytics, and reporting within cloud-based environments.

Proven experience leading technical projects from intake through design, development, and implementation.

Demonstrated ability to translate business needs and stakeholder requests into complex technical requirements.

Advanced proficiency in SQL and Python for data…