Engineering Manager, Data & AI Governance

Crown Castle Ltd; Houston (TX); Hybrid; USD 128,000 - 168,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Tuition reimbursement

Scholarship program

Paid time off

Holidays and snacks

Job summary

Crown Castle is seeking a Manager of Engineering for Data & AI Governance to lead a transformation of governance from manual to automated, scalable, and AI-ready. You will architect and drive the engineering strategy, automation, and operating practices across data products, pipelines, and platforms, partnering with security, legal, risk, and business teams.

The role emphasizes hands-on leadership in Databricks, data quality, metadata, lineage, and policy automation, with a hybrid in-office

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics, Physics, Computational Science, or another highly quantitative discipline.
• Master’s or a PhD in a relevant quantitative or computational discipline preferred.

Responsibilities

• Establish and execute the roadmap to build a best-in-class Data & AI Governance Engineering capability.
• Deliver measurable improvements in data quality, trust, ownership, lineage, accessibility, security, and AI readiness.
• Balance long-term governance vision with rapid execution against top business priorities.
• Embed governance by design into data products, pipelines, semantic models, and platform services.
• Implement and automate metadata, lineage, classification, access, quality, observability, and governance capabilities.

Skills

Python

SQL

Data governance

Data quality

Leadership

Education

Bachelor's degree in a quantitative field

Master's or PhD preferred

Tools

Databricks

Unity Catalog

CI/CD

Job description

Crown Castle is seeking a Manager of Engineering for Data & AI Governance to lead a transformation of governance from manual to automated, scalable, and AI-ready. You will architect and drive the engineering strategy, automation, and operating practices across data products, pipelines, and platforms, partnering with security, legal, risk, and business teams.

The role emphasizes hands-on leadership in Databricks, data quality, metadata, lineage, and policy automation, with a hybrid in-office