Enterprise AI & Analytics Product Leader

Heidelberg Materials North America; Irving (TX); Hybrid; USD 136,000 - 181,000; Full time

Benefits offered by this job

401(k) plan

Medical/Dental/Vision

HSA/HRA/FSA

Job summary

Heidelberg Materials North America seeks a senior analytics leader to drive enterprise Databricks adoption and AI-enabled data products. You will partner with Finance, Operations, Digital, and Data Engineering to deliver scalable analytics use cases and govern metrics across the organization.

Lead cross-functional programs, define semantic models, and enable trusted, self-service insights through governance and robust data platforms. Occasional travel may be required.

Qualifications

• Bachelor's degree or higher in a relevant field (Business, Analytics, CS, Engineering).
• 5+ years in analytics, BI, data platforms, or digital transformation with business value delivery.
• 3+ years leading cross-functional initiatives with business and data teams.

Responsibilities

• Lead enterprise adoption of Databricks analytics, AI/BI, and related technologies to generate business value.
• Partner with Finance, Commercial, Operations, Digital and Data Engineering to deliver high-impact analytics use cases.
• Own the strategy, roadmap and lifecycle of business-facing data and AI products from discovery to deployment and value realization.
• Establish KPI definitions, semantic models, and metric standards for trusted insights across reporting and AI solutions.
• Drive AI-powered decision-making with conversational analytics, NLQ, and AI-generated insights to reduce manual reporting.
• Champion data governance and standardization to ensure trusted metrics and reusable data assets.

Skills

Databricks

AI/BI

Stakeholder management

Data governance

Education

Bachelor's degree or higher

Job description

Heidelberg Materials North America seeks a senior analytics leader to drive enterprise Databricks adoption and AI-enabled data products. You will partner with Finance, Operations, Digital, and Data Engineering to deliver scalable analytics use cases and govern metrics across the organization.

Lead cross-functional programs, define semantic models, and enable trusted, self-service insights through governance and robust data platforms. Occasional travel may be required.