Manager, Data Engineering - Data & AI Governance

External Crown Castle Careers • Houston, TX

11h • Hybrid

About The Position

The Manager of Engineering – Data & AI Governance is a forward-looking, highly technical, and relentlessly execution-oriented individual who will build a best-in-class governance and data quality capability over the next several years. This is not a traditional governance oversight role, and isn’t centered on administering committees, producing policy documents, or manually tracking compliance. This leader will establish the strategy and personally drive the engineering, automation, operating practices, and organizational adoption required to make trusted, governed, and AI-ready data an embedded characteristic of our enterprise data ecosystem. The mandate is not simply to operate governance more efficiently, but to fundamentally transform governance from a predominantly manual and reactive activity into an intelligent, continuous, measurable, and increasingly automated capability, using modern technology, reusable engineering patterns, and artificial intelligence. Data governance and data quality will be the immediate priorities. The role will also build and mature AI governance in parallel with enterprise AI adoption, creating pragmatic guardrails that manage risk without unnecessarily slowing experimentation, innovation, or business value. The ideal candidate brings meaningful experience in software engineering, data engineering, analytics engineering, and/or other closely related technical disciplines. We are searching for a builder who sees governance as a product and an engineering challenge, not an administrative function, and someone who is energized by an ambitious target, impatient with unnecessary manual work, and willing to personally solve difficult problems. They do not need to be an expert in data management or governance technology, but they must have technical capacity, curiosity, passion, and drive to work hands-on in leading data and AI governance and quality.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics, Physics, Computational Science, or another highly quantitative discipline.
• 7 or more years’ experience with a Masters, or 5 or more years’ experience with a Master’s or PhD, of progressively advanced experience across software engineering, data engineering, analytics engineering, data platforms, data governance, data quality, and/or related disciplines.
• A passion and enthusiasm for data, AI, data governance, data management, and data quality.
• Demonstrated ability to lead strategy while remaining personally engaged in technical execution.
• Strong understanding of modern data architecture, data pipelines, data models, metadata, lineage, access controls, data quality, testing, and observability.
• Working proficiency in one or more technical languages, preferably Python and SQL.
• Experience automating technical or operational processes through code, APIs, workflow orchestration, CI/CD, and/or platform capabilities.
• Ability to work hands-on in a modern cloud data environment and quickly learn new technologies.
• Strong judgment, analytical problem-solving, attention to detail, and personal accountability.
• Ability to influence across engineering, analytics, architecture, security, legal, risk, audit, and business organizations.

Nice To Haves

• Master's or a PhD in a relevant quantitative or computational discipline preferred.
• Experience preferred with Databricks, Unity Catalog, and associated technologies.
• Experience preferred implementing data quality, data observability, metadata management, cataloging, lineage, classification, or policy automation.
• Experience preferred applying software engineering practices to data or governance capabilities, including source control, automated testing, deployment pipelines, infrastructure as code, or reusable frameworks.
• Experience or familiarity preferred with data products, data contracts, semantic layers, federated governance, and self-service data access.
• Experience preferred with responsible AI, AI risk management, model governance, generative AI governance, and/or agent governance.

Responsibilities

• Establish and execute the roadmap to build a best-in-class Data & AI Governance Engineering capability at Crown Castle.
• Deliver measurable improvements in data quality, trust, ownership, lineage, accessibility, security, and AI readiness by applying modern practices and eliminating manual, bureaucratic processes.
• Balance the long-term governance vision with rapid execution against the highest-priority business needs, by introducing modern practices that improve speed, scale, quality, and business value.
• Embed governance by design into data products, pipelines, semantic models, and platform services in partnership with technical, security, audit, and business teams.
• Implement and automate metadata, lineage, classification, access, quality, observability, and governance capabilities across Databricks and the broader data ecosystem.
• Create reusable standards, controls, and reference patterns while remaining hands-on in prototyping, configuring, testing, troubleshooting, and improving critical capabilities.
• Build an automation-first governance strategy that enables a small team to deliver enterprise-scale impact through modern technology and AI.
• Develop intelligent workflows and assistants that guide data owners and stewards, automate routine decisions, and reduce the effort required to fulfill governance responsibilities.
• Create measurable, exception-based operations that automatically surface risks, prioritize issues, route accountability, and focus the team on the areas requiring human judgment.
• Establish clear, measurable expectations for trusted data products, including ownership, business meaning, quality, classification, service levels, and approved use.
• Enable users to confidently discover, understand, evaluate, and access governed data through an intuitive enterprise catalog and transparent quality information.
• Drive cross-functional resolution of systemic data quality issues by addressing root causes and strengthening accountability at the source.
• Establish an enterprise inventory and lifecycle governance model for machine learning, generative AI, agents, and intelligent automation, from initial use-case evaluation through retirement.
• Apply proportionate, risk-based governance that accelerates lower-risk innovation while strengthening controls for sensitive data, automated actions, consequential decisions, and material enterprise risks.
• Partner across Legal, Security, Privacy, Risk, Audit, Architecture, and the business to establish clear review, approval, monitoring, and accountability for enterprise AI solutions.

Benefits

• Comprehensive healthcare plans with highly company subsidized premiums and up to $2,000 annual company contribution to your Health Savings Account (HSA base plan for employee and dependents).
• Market-leading 401(k) plan, which includes up to 10% company contributions through our 5% match and 5% profit sharing program (based on employee contributions).
• New-child leave up to 8 weeks of 100% paid leave upon birth or legal adoption of a new child.
• Birth mothers are eligible for up to 8 weeks of additional 100% paid medical leave.
• Tuition reimbursement up to $5,250 per year of eligible tuition and fees.
• Crown Castle scholarship program awarding up to $10,000 per recipient each year for eligible dependent children of employees and interns.
• Matching charitable contributions to qualified charitable organizations of up to $1,000 per year per teammate.
• Generous paid time-off for eligible full-time employees (minimum 18 days per year based on years of service).
• 10 company holidays plus 2 floating holiday.
• All offices provide free beverages and snacks.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager