The Zekelman Holocaust Center

The Zekelman Holocaust Center

Head of Data Enablement

Remote_USA, USA · Full-time

Sponsorship not specified$142k-$255kDetected 61 days ago
PythonSQLSnowflakeDatabricksAWSGCPAzureCloud PlatformsMachine LearningData EngineeringData ScienceStakeholder ManagementCRMSupply ChainERPLeadershipCommunication

About the role

  • As the Head of Data Enablement at Zekelman Industries, you will lead the transformation of the organization's data capabilities, evolving from traditional data management to treating data as a strategic enterprise asset. This role is responsible for designing, building, and scaling a new enterprise data management function that supports AI, advanced analytics, and data-driven decision-making across the business.
  • You will collaborate closely with leadership, technical teams, and business stakeholders to establish data strategy, architecture, governance, and operating models that unlock value from manufacturing, commercial, and supply chain data.
  • This role is ideal for a hands-on data leader who has evolved from technical architecture into enterprise leadership and is passionate about building high-impact data organizations from the ground up.

Responsibilities

  • Design foundational data architecture including cloud data platforms, data warehouses or lakehouses, and integration layers.
  • Build and scale the enterprise data function, including hiring and developing data architects, engineers, analysts, and stewards.
  • Evaluate and implement modern data platforms and tools including cloud infrastructure, integration tools, and data management systems.
  • Partner with business and technology teams to translate data into actionable insights and operational value.
  • Develop disaster recovery, business continuity, and data protection strategies.
  • Perform other duties as assigned.

Requirements

  • 10+ years of progressive experience in data management, architecture, or analytics, including leadership experience.
  • Proven experience evolving from hands-on data architecture into enterprise data leadership.
  • Hands-on experience with cloud data platforms (Azure, AWS, or GCP) and modern data technologies such as Databricks, Snowflake, or Microsoft Fabric.
  • Experience integrating enterprise systems such as ERP, CRM, MES, and WMS into analytics platforms.
  • Strong knowledge of data governance, data quality, and master data management practices.
  • Proficiency in SQL, Python, and modern data engineering tools.
  • Ability to influence both technical and non-technical audiences at all levels of the organization.
  • Lead and promote healthy and safe work practices as required by regulatory agencies and Company policy.

Nice to have

  • Bachelor's degree in Computer Science, Data Science, Engineering, or related field preferred
  • advanced degree preferred.
  • Strong background in manufacturing, industrial, or asset-heavy environments
  • steel industry experience preferred.

Compensation

  • [$ 142,140-$ 255,440 USD]
  • Additional compensation may include:
  • Zekelman Industries offers competitive compensation and excellent benefits, including low-cost, high-quality medical and dental benefits.
  • Below is the expected base salary range for this position.

Benefits

  • Zekelman Industries offers competitive compensation and excellent benefits, including low-cost, high-quality medical and dental benefits.
  • In addition, we have an amazing tuition assistance program, a bonus plan, a 401(k) plan with a generous company match, loyalty awards, and much more:
  • Bonus Plan & Profit-Sharing Opportunities
  • Comprehensive Health, Dental & Vision Insurance
  • Paid Vacation & Holidays
  • Ensure data is structured and accessible to support AI, machine learning, and advanced analytics use cases.
  • ✔ Profit-sharing bonus opportunities
  • In addition, we have an amazing tuition assistance program, a bonus plan, a 401(k) plan with a generous company match, immediate vesting, and much more.

This listing is sourced directly from The Zekelman Holocaust Center's careers page and normalized into a canonical job model.