Senior Governance Architect

About Lumenalta

At Lumenalta, we partner with forward-thinking organizations to build technology solutions that scale, delight users, and accelerate business growth. Our global teams bring curiosity, commitment, and technical excellence to every project. We value transparency, autonomy, and impact, empowering every team member to do their best work.

About the Role

We are looking for a Senior Governance Architect to own the governance architecture on a strategic enterprise data modernization engagement for a global industrial manufacturing client. The client is defining its target-state data platform across Microsoft Fabric and Azure Databricks, and governance is at the center of it: the business needs to trust its data before it can run analytics and AI on it.

This is not a traditional catalog-and-lineage role. The client is building toward GenAI and agentic AI on its enterprise and plant data, so governance has to reach beyond tables and pipelines to AI models, prompts, and agents. You will partner with our AI Lead on the AI readiness assessment and own the AI governance framework. If you have done solid governance work on Unity Catalog or Purview and want to apply it to the AI governance problems most organizations are only starting to face, this role is built for that.

The foundation is still rigorous data governance: assessing the client's current capabilities against an eight-component framework, evaluating the governance technology stack, and designing the enabling architecture for metadata, catalog, lineage, data quality, reference data, and master data management (MDM), including Stibo STEP integration. The client has its own governance team that owns policies and stewardship, so you will need the tact to complement their work rather than overlap it.

What You'll Be Doing

• Governance capability assessment. Assess the client's current governance capabilities against an eight-component framework, score maturity, identify gaps, and translate the findings into a prioritized governance capability roadmap.
• Governance technology evaluation. Define weighted evaluation criteria, compare catalog, lineage, glossary, data quality, and MDM tooling, and recommend a stack that works across both Fabric and Databricks.
• Enabling architecture. Design the governance architecture for metadata, catalog, business glossary, lineage, data quality, reference data, and MDM, and show how each capability is enforced in the recommended tooling.
• Data catalog and glossary. Architect the catalog strategy with Microsoft Purview and Unity Catalog, covering catalog and schema structure, classification, business glossary, and discoverability across Fabric and Databricks.
• Lineage. Design end-to-end lineage from source systems through the medallion layers (Bronze, Silver, Gold) to reporting, so every number can be traced back to its origin.
• Data quality. Define the data quality architecture: rule definition, monitoring, and remediation workflows, backed by the tooling recommendation.
• Classification and sensitive data. Define the data classification scheme and sensitive data handling in the catalog, and how fine-grained access controls in Purview and Unity Catalog enforce them, aligned with the security architecture and the client's compliance requirements.
• Reference data and master data. Design how reference data and master data from Stibo STEP are governed and integrated with the lakehouse, keeping product, customer, and material data consistent across enterprise and plant systems.
• SAP and plant data. Extend the governance model to SAP data (replicated through SAP SLT) and to operational technology data from plant systems, so it is catalogued, traced, and quality-checked like any other domain.
• AI governance. Partner with the AI Lead on the AI and GenAI maturity assessment and use case prioritization, and own the AI governance framework recommendation: how data access, lineage, quality, and classification controls extend to AI models, prompts, retrieval, and agents, and what guardrails the client needs before agentic AI runs on production data.
• Client governance team partnership. Coordinate closely with the client's governance team, clarify where their work ends and ours begins, and support their goals without duplicating effort.
• Communication. Present governance findings, decisions, and trade-offs in workshops and executive readouts, in clear, practical terms for both engineers and business stakeholders.

What We're Looking For

• 7+ years of experience in data governance, data architecture, or data management roles, with hands-on ownership of governance programs on enterprise data platforms.
• Proven experience assessing governance maturity and designing governance architectures: metadata, catalog, glossary, lineage, data quality, reference data, and MDM.
• Hands-on experience with both Microsoft Purview and Unity Catalog for cataloging, lineage, and access control, and with integrating governance across Fabric and Databricks.
• Hands-on experience on both Microsoft Fabric and Azure Databricks, with working knowledge of lakehouse and medallion architecture on Azure.
• Experience running structured technology evaluations: defining criteria, comparing tools, and defending a recommendation to senior stakeholders.
• Experience selecting and designing data quality tooling, including rule definition, monitoring, and remediation.
• Experience with MDM, including data models, matching, and integration with downstream platforms.
• Familiarity with AI governance: extending data governance controls to machine learning and GenAI workloads, and working alongside MLOps and AI teams.
• Consulting or client-facing delivery experience, including facilitating workshops and presenting findings and recommendations to senior stakeholders.
• Strong collaboration skills to work alongside an existing client governance team.
• Advanced English and the ability to communicate clearly with engineers and business stakeholders.

Nice to Have

• Hands-on experience with Stibo STEP (strongly preferred).
• Experience governing SAP data, particularly data replicated through SAP SLT.
• Experience with OT data in manufacturing or industrial environments, including PLC, SCADA, MES, and historian systems, and streaming sources such as OPC UA and MQTT.
• Familiarity with data governance frameworks such as DAMA DMBOK or DCAM.
• Experience with AI readiness assessments, AI use case prioritization, or MLOps practices.
• Prior client-facing delivery in manufacturing, aerospace, finance, e-commerce, or logistics.
• Certifications such as CDMP, Databricks Certified Data Engineer Professional, Microsoft Certified: Fabric Data Engineer Associate, or Microsoft Certified: Information Protection and Compliance Administrator Associate.
• A degree in Computer Science, Information Systems, Engineering, or a related field; a Master's degree is a plus.

Why Lumenalta is an amazing place to work at

At Lumenalta, you can expect that you will:

• Be 100% dedicated to one project at a time so that you can innovate and grow.
• Be a part of a team of talented and friendly senior-level developers.
• Work on projects that allow you to use leading tech.

Location

This is a fully remote position open to candidates based anywhere in the Americas (North, Central, and South America); candidates must be able to work with full overlap with U.S. business hours to ensure effective collaboration with client and team schedules.

Application Deadline

Applications will be accepted until November 19, 2026. Candidates can expect feedback by November 23, 2026.