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GLO - Senior Data Engineer (Programmer V)Centralized Accounting and Payroll/Personnel System • Austin, Texas, United States
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GLO - Senior Data Engineer (Programmer V)

Centralized Accounting and Payroll/Personnel System
  • US
    Austin, Texas, United States
  • US
    Austin, Texas, United States
Postuler Maintenant

À propos

Overview The Texas General Land Office is seeking a Senior Data Engineer (Programmer V) within its Information Technology Services Department. The role involves advanced computer programming, software engineering, and technical leadership to design, develop, test, and maintain complex data platform solutions across the agency’s data and analytics ecosystem.
Responsibilities
Provide technical leadership across data platform domains or shared platforms, shaping and applying domain‑level standards, patterns, and delivery practices.
Design, develop, test, and maintain complex data engineering solutions, including pipelines, integration tools, and modern warehouse environments such as Snowflake and Databricks.
Address ambiguous or novel technical problems requiring advanced analysis and judgment, ensuring consistency, reliability, maintainability, and SDLC alignment across related applications or services.
Lead code and design reviews, mentor peers through hands‑on collaboration, and provide technical guidance without formal supervisory responsibilities.
Execute quality, reliability, and operational support activities, including system analysis, incident response, automation, tooling, and process improvements.
Qualifications
Bachelor’s degree in computer science, information systems, computer engineering, or related field; or equivalent professional experience (one year of experience per year of education).
Four (4) years of professional experience in data engineering, including designing, developing, implementing, and maintaining data pipelines and enterprise data platforms.
Preferred Qualifications
Experience supporting data platform modernization, including migration of legacy systems to cloud‑based environments.
Experience implementing data quality controls, monitoring processes, and operational support procedures for enterprise data pipelines.
Experience working with large‑scale structured and semi‑structured data in batch and distributed processing environments.
Familiarity with data governance concepts, metadata management, data lineage, and regulatory compliance requirements.
Proficiency in SQL, Python, Spark, or similar technologies for data engineering and processing workloads.
Relevant industry certifications in cloud technologies, data engineering, analytics, or database platforms.
Technical Knowledge
Modern data platform architectures (cloud‑based warehouses, distributed processing).
Data warehousing concepts, dimensional modeling, and reporting data structures.
ETL/ELT methodologies, data integration patterns, and orchestration tools.
Data governance principles, including quality, metadata management, and lineage tracking.
Database design, performance tuning, and data optimization techniques.
Security, privacy, and compliance considerations for enterprise data environments.
Skills
Design, develop, and maintain scalable data pipelines and integration solutions.
Build and support cloud‑based data warehouses and modern data platforms.
Develop data transformation processes using SQL, Python, Spark, or similar tools.
Implement data quality validation, monitoring, and operational support processes.
Troubleshoot and resolve complex data integration, performance, and reliability issues.
Create technical documentation, solution designs, and operational procedures.
Abilities
Serve as a senior technical contributor on complex data engineering initiatives.
Collaborate effectively with architects, analysts, developers, business stakeholders, and project teams.
Exercise sound judgment in designing and implementing enterprise data solutions.
Translate business, operational, and reporting requirements into reliable and scalable data pipelines.
Support data modernization efforts while maintaining operational stability and performance.
Mentor and provide technical guidance to less experienced team members while promoting data engineering best practices.
Physical Requirements The position requires primarily sedentary office work but involves routine mobility to carry out duties, including moving and transporting records, documents, boxes, and materials weighing up to 20 pounds. The role requires extensive computer, telephone, and client/customer communication, and the stamina to maintain attention to detail despite interruptions.
Compensation & Benefits
Free parking.
Defined Retirement Benefit Plan, optional 401(k) and 457 accounts.
Medical insurance – state pays 100% of the premium for eligible full‑time employees and 50% for eligible dependents; 50% for part‑time employees and 25% for dependents.
Optional benefits such as dental, vision, and life insurance.
Minimum 96+ hours of annual leave, increasing with length of service.
Professional development opportunities through LinkedIn Learning and EAP provider.
Application Process Applicants must submit a fully completed application with a detailed job history, including job title, employment dates, employer name, supervisor’s name and phone number, and a summary of responsibilities. Incomplete applications may lead to disqualification. Resumes will not be accepted in place of a completed application. Applications must verify identity and employment eligibility upon hire. This position is security sensitive per Texas Labor Code Section 301.042. Applicants must be authorized to work for any U.S. employer; no visa sponsorship is available.
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  • Austin, Texas, United States

Compétences linguistiques

  • English
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