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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Governance Engineer - **Company:** Tenaska - **Location:** Omaha, NE, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Database, Program Optimization, Information Systems, Computer Programming, Data Architecture, Data Cleansing, Data Discovery, Information Engineering, Data Governance, Data Security, Dataspaces, Data Warehousing, Revision Control Systems, Intrusion Detection and Prevention, Python (Programming Language), Meta-Data Management, Cloud Services, Software Engineering, Software Systems, SQL Databases, Technical Data Management Systems, Enterprise Data Management, Large Language Models, Snowflake, Data Strategy, Microsoft Fabric, Information Technology, Data Management, Software Version Control, Data Pipelines, Databricks - **Published:** July 10, 2026 - **Apply:** https://recruiting.ultipro.com/TEN1001TEINC/JobBoard/52989607-07f5-4be5-b6f7-1878fa879db5/OpportunityDetail?opportunityId=eb12ca8e-1e73-467d-9097-2003dca17c98 ## About the Role * 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 * Experience working with modern data ecosystems, including cloud data platforms such as: * + Microsoft Fabric + Snowflake + Databricks * Cloud data lakehouse and enterprise data warehouse architectures * Experience developing automated data quality frameworks, controls, monitoring, and validation processes. * Experience with metadata management, data cataloging, lineage, or data discovery solutions. * Understanding of master data management (MDM) concepts and enterprise data governance practices. * Experience collaborating with both technical teams and business stakeholders to drive data adoption and accountability. Preferred Qualifications: * 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 * + Experience with data catalog platforms such as Atlan or Data.world. + Experience with MDM platforms. + Experience implementing governance practices within complex enterprise environments. + Strong understanding of data security, compliance, and risk management principles. ## Description 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. * Help define requirements and evaluate solutions that support enterprise data strategy. Drive Data Governance Adoption * Act as a bridge between technical teams, business stakeholders, data owners, data stewards, and risk/compliance partners. * Translate complex governance concepts into clear, practical processes that enable adoption across the organization. * Promote a culture of data ownership, accountability, and trust through self-service governance practices. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Harnessing the Power of Open Source's Newest Technologies](https://www.wearedevelopers.com/videos/1448-harnessing-the-power-of-open-source-s-newest-technologies) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence)