Enterprise AI Product Lead - Data Strategy & Adoption

Heidelberg Materials

Irving (TX)

Hybrid

USD 136,000 - 181,000

Full time

14 days+

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Benefits offered by this job

401(k) matching
Competitive salary
Comprehensive benefits

Job summary

Heidelberg Materials North America is seeking a senior analytics leader to drive enterprise adoption of Databricks analytics, AI/BI, and related data products. You will own the strategy, roadmap, and lifecycle of business-facing data assets, partnering with Finance, Operations, Digital, and Data Engineering to deliver high-impact use cases and measurable value.

The role requires a strong background in analytics, KPI governance, and stakeholder management, with a hybrid work environment and

Qualifications

  • Bachelor's degree in a related field; advanced degrees or certifications preferred.
  • 5+ years in analytics, BI, data products or related disciplines with business value delivery.
  • Experience translating priorities into scalable data products and dashboards.

Responsibilities

  • Lead enterprise adoption of Databricks analytics, AI/BI, and related technologies.
  • Partner with Finance, Commercial, Operations, Digital, and Data Engineering to deliver high-impact use cases.
  • Own strategy, roadmap, and lifecycle of data products and KPI definitions.
  • Govern semantic models, metrics, and reusable data assets across platforms.
  • Enable AI-driven decision making with conversational analytics and actionable insights.
  • Champion data governance and quality to ensure trusted metrics and explainable AI.
  • Drive adoption through change management, training, and cross-functional collaboration.

Skills

Stakeholder mgmt
Data storytelling
Analytics leadership

Education

Bachelor's degree

Tools

Databricks
Snowflake
Azure data platforms
Microsoft Fabric

Job description

Heidelberg Materials North America is seeking a senior analytics leader to drive enterprise adoption of Databricks analytics, AI/BI, and related data products. You will own the strategy, roadmap, and lifecycle of business-facing data assets, partnering with Finance, Operations, Digital, and Data Engineering to deliver high-impact use cases and measurable value.

The role requires a strong background in analytics, KPI governance, and stakeholder management, with a hybrid work environment and

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