This is a highly visible, foundational role reporting to the CIO and sitting at the center of Crystal Clean's transformation agenda.
As Director of Data & AI, you will define and implement the enterprise data strategy, establishing KPI standards, governance frameworks, and a unified data operating model across a distributed network of field operations and business functions. You will act as the bridge between business leaders, IT, and external partners, ensuring data is accurate, consistent, and directly tied to operational decision-making.
This is not a traditional IT or data engineering role. Crystal Clean is seeking a business-first operator who uses data and AI to drive real-world outcomes, not just build infrastructure. The ideal candidate brings a consulting-style mindset, is comfortable translating ambiguous business problems into structured, data-driven actions, and has a demonstrated track record of deploying AI to create measurable business value. Crystal Clean has begun its AI journey. This role is responsible for accelerating it.
Essential Functions
- Shape enterprise data strategy by developing and executing a comprehensive roadmap to unify data across systems and functions, creating the foundation on which AI can operate at scale.
- Standardize KPIs and metrics by creating a company-wide framework aligned with business performance and decision-making, replacing inconsistent, function-specific definitions with a single source of truth.
- Establish data governance by defining ownership, data contracts, and governance processes that improve data quality and accountability across the organization.
- Improve data quality at the source by partnering with operations and finance teams to resolve root-cause issues within ERP and plant systems, rather than managing problems downstream.
- Lead post-acquisition data integration by building scalable and repeatable processes to onboard acquired businesses into a standardized data model as Crystal Clean continues to grow inorganically.
- Translate insights into impact by working closely with business leaders to drive measurable operational improvements across plants and functions, moving beyond reporting to execution.
- Accelerate enterprise AI adoption by owning the AI roadmap, identifying high-value use cases across operations, finance, and commercial functions, and driving them from concept to production. This includes generative AI, predictive analytics, and intelligent automation, prioritized by business impact and operational readiness.
- Oversee external partners, including data platform vendors, AI solution providers, and offshore teams, ensuring outputs align with business needs and quality standards.
- Enable scalable decision-making by building a strong foundation for consistent reporting, performance tracking, and an AI-enabled enterprise.
Essential Qualifications
- 8 to 12 or more years of experience in data, analytics, strategy, or AI roles with a strong operational focus.
- Proven ability to translate data into measurable operational improvements, well beyond reporting and dashboards. Demonstrated experience deploying AI solutions in an enterprise environment, not evaluating them but delivering them.
- A clear and defensible point of view on where AI creates operational leverage in field services, logistics, or similarly complex operating environments.
- Strong cross-functional leadership across operations, finance, commercial, and IT teams. Comfort operating in fast-paced, ambiguous environments while bringing structure to fragmented systems and competing priorities.
- Strong stakeholder management skills, with demonstrated ability to influence both frontline operational leadership and executive teams.
- Ability to speak to specific AI use cases they have owned and delivered will stand out significantly.
Work Environment
This role primarily operates in an office environment and requires prolonged periods of sitting, working on a computer, and communicating via phone and email. The position may require occasional standing, walking, and use of standard office equipment.
The noise level is typically moderate. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Crystal Clean LLC is an Equal Opportunity Employer. Crystal Clean expressly values diversity, equity, and inclusion, and encourages the applications of individuals from diverse backgrounds, so that Crystal Clean reflects the communities and customers that we serve.
The anticipated hourly range for this position is $191,180.00 – $216,000.00 and includes benefits such as the following:
- Health, Dental and Vision insurance
- Wellness Program
- Flexible Spending Accounts
- Life Insurance
- Long-Term Disability
- Employee Assistance Program
- Tuition Reimbursement
Skills Required
- 8 to 12+ years in data, analytics, strategy, or AI roles with strong operational focus
- Proven track record deploying AI solutions in enterprise environments (delivered to production)
- Experience translating data into measurable operational improvements beyond reporting
- Experience defining and implementing data governance, ownership, and data contracts
- Experience standardizing KPIs and creating a single source of truth across functions
- Experience leading post-acquisition data integration and onboarding into standardized data models
- Strong cross-functional leadership and stakeholder management across operations, finance, commercial, and IT
- Ability to speak to specific AI use cases owned and delivered (examples/case studies)
What We Do
Heritage-Crystal Clean, LLC (HCC) is a national leader in the environmental services market, providing the smart alternative. Founded in 1999 by a team of seasoned industry professionals, HCC operates a nationwide network of branches serving the continental United States. HCC operates more than 85 service branches across the nation and multiple waste recovery centers, including an oil re-refinery, regional antifreeze recovery centers, and several waste water treatment facilities. HCC disposes of waste it collects in an environmentally sustainable way, focusing on recycling waste for reuse or disposing of in a waste-to-energy process.

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