Data Governance Engineer
- Compensation
- Not disclosed
- Location
- Omaha, Nebraska, United States
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 4+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
- 4–6 years of experience in data engineering, software engineering, or a highly technical data management role.
- Experience designing, developing, and deploying production-grade software solutions.
- Strong programming experience with:
- Python SQL APIs Version control tools (Git/GitHub) Software Development Life Cycle (SDLC) practices
Nice to have
- Experience building AI agents or intelligent automation solutions using: Large Language Models (LLMs) Enterprise APIs Model Context Protocol (MCP) AI coding tools and developer platforms
Full description
Tenaska is one of the largest privately held companies in the United States, an organization that’s adept in natural gas and power marketing, power management, development and acquisition of generation assets, operation of power plants and more.
Onsite: Omaha, NE or Irving, TX
Position Summary:
Tenaska is seeking a Data Governance Engineer to help transform our enterprise data governance model from a traditional, manual approach into a modern, automated operating model powered by engineering practices and artificial intelligence.
This role will sit at the intersection of software engineering, data engineering, AI automation, and enterprise data management. The ideal candidate will build intelligent solutions that automate governance processes, improve data quality, strengthen metadata management, and enable teams across the organization to confidently leverage trusted data.
The Data Governance Engineer will play a key role in designing and implementing automated governance frameworks, developing AI-driven solutions, and partnering with technical and business stakeholders to create a scalable data ecosystem.
Essential Job Functions:Automate Data Governance Processes
- Develop AI agents and workflow automation solutions using AI coding tools, large language models (LLMs), APIs, Model Context Protocol (MCP), and enterprise data sources.
- Design and implement automated governance controls directly within data pipelines to ensure trusted, compliant, and high-quality data reaches enterprise users and AI systems.
- Develop Policy-as-a-code functions using modern engineering practices, including version control, testing, and deployment processes.
Advance Metadata Management & Data Discovery
- Build and maintain automated metadata management frameworks to improve data cataloging, lineage visibility and data product management.
- Implement and enhance enterprise data catalog capabilities through active metadata management and automated discovery frameworks.
Improve Data Quality & Reliability
- Build and maintain automated data quality frameworks that proactively identify issues and anomalies.
- Implement monitoring, telemetry, alerting, and data drift detection capabilities.
- Evaluate and optimize data quality tools and processes to improve enterprise data trust.
Support Data Architecture & Platform Optimization
- Partner with data engineering teams to optimize governance capabilities across modern cloud data platforms.
- Support administration and continuous improvement of enterprise data catalog, data quality, and master data management (MDM) platforms.