Data Engineer (SR)

Lead end-to-end enterprise data engineering efforts, from pipeline and reporting foundations to data governance and AI operationalization.

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.
• Create and maintain data models, including dimensional and semantic models, to keep enterprise data usable and consistent for reporting and analytics.
• Develop and tune complex SQL transformations and queries using SQL, PL/SQL, T-SQL, and Python to support ETL and ELT processes.
• Build and maintain reliable data repositories with 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, including 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: 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 covering data quality, classification, retention, and access controls aligned with organizational policies and Texas records retention requirements.
• Ensure proper data usage controls for AI, including approved data sources, privacy requirements, 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 stakeholder needs 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 help build analytics capability among business users.
• Collaborate using Agile methodologies and tools such as JIRA, Confluence, and Git.
• Investigate new technologies and assess their viability for 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.
• Provide after-hours support as needed; other duties as assigned.
• Follow all applicable policies and procedures, including all security policies.

Requirements

• Bachelor’s degree in data science, computer science, information systems, engineering, actuarial science, mathematics, statistics, or related field.
• Minimum 7 years 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 SQL and Python proficiency for data engineering, transformation, and analysis.
• Strong written and verbal communication skills to convey complex technical concepts to non-technical stakeholders.

Technologies

• SQL, PL/SQL, T-SQL, Python
• Azure, AWS
• Power BI
• Azure Synapse Analytics
• JIRA, Confluence, Git
• ETL, ELT
• MLOps
• Microsoft Azure Data certifications, Microsoft Azure AI certifications

Benefits

• Participation in TMRS pension plan with a 2:1 organization match.
• Optional 457(b) deferred compensation plan participation.
• Medical, dental, and vision insurance at no cost to employees.
• Hybrid work opportunities; 12 paid holidays; generous leave.
• Modern, centrally located Austin office.
• Onsite presence required a minimum of three days per week; remote work opportunities exist, but this is not a remote position.
• Starting base salary (based on experience and qualifications).

Education & Experience

• Hands-on experience with Advanced SQL (Oracle PL/SQL and T-SQL) and Python for data engineering, transformation, and analysis.
• Hands-on experience with cloud data platforms and services (Azure and AWS), including storage, compute, and managed data services.
• Hands-on experience with ETL and ELT pipeline design, orchestration, and scheduling.
• Hands-on experience with data warehouse, lakehouse, and dimensional modeling.
• Hands-on experience with business intelligence and reporting platforms (Power BI or equivalent).
• Hands-on experience with data governance: classification, lineage, retention, and access control.
• Hands-on experience with machine learning model integration and lifecycle management (MLOps).
• Hands-on experience with Agile delivery tooling: JIRA, Confluence, and Git-based source control.

Preferred

• Previous implementation of data and analytics solutions using Microsoft Power BI and Azure Synapse Analytics.
• Experience implementing large language models with model versioning, including prompt and version control, evaluation tracking, continuous monitoring, and deployment lifecycle management.
• Experience sourcing data from Oracle and SQL Server based systems of record.
• Experience with data cataloging, master data management, or metadata management tooling.
• Streaming or near-real-time data integration.
• Public sector, pension administration, or financial services environment subject to SOC or NIST-based control requirements.
• Experience supporting actuarial, investment, or financial reporting data needs.

Certificates & Licenses

• Microsoft Azure Data certifications are preferred.
• Microsoft Azure AI certifications are preferred.

Qualities We Are Looking For

• Confident and mature leadership skills.
• Highest level of character and integrity.
• Executive presence and strength of character.
• Excellent interpersonal and relationship skills.
• Intellectual curiosity and determination.
• Team orientation, integrity, and strong work ethic.
• Effective communication: listens carefully, asks effective questions, articulates clearly and concisely.
• Self-driven with strong attention to detail and structured problem-solving in a collaborative team environment.

Physical Requirements

• Sedentary work: exerting up to 10 pounds of force; able to perform essential job functions safely and successfully consistent with federal, state, and local standards.