Director, Enterprise Data Strategy & Business Insights

ALKEGEN•Dallas, TX

About The Position

Alkegen brings together two of the world’s leading specialty materials companies to create one new, innovation-driven leader focused on battery technologies, filtration media, and specialty insulation and sealing materials. Through global reach and breakthrough inventions, we are delivering products that enable the world to breathe easier, live greener, and go further than ever before. With over 60 manufacturing facilities with a global workforce of over 9,000 of the industry’s most experienced talent, including insulation and filtration experts, Alkegen is uniquely positioned to help customers impact the environment in meaningful ways. Alkegen offers a range of dynamic career opportunities with a global reach. From production operators to engineers, technicians to specialists, sales to leadership, we are always looking for top talent ready to bring their best. Come grow with us! The Director of Enterprise Data Strategy & Business Insights is a business-facing senior leader responsible for establishing and driving a business-aligned data and analytics capability across Alkegen. The role will report directly to the CIO and work closely with the Technical Director of Data & Analytics, who focuses on the technical deliverables. Building on existing technical data foundations, this role operates at the intersection of business processes, data, and analytics, ensuring that enterprise data is clearly defined, trusted, and aligned to business decision-making. This leader will focus on understanding and mapping core business processes (Finance, Supply Chain, Manufacturing, Commercial) and translating them into standardized data definitions, KPIs, and governed data products. The role is critical to moving the organization away from fragmented reporting and inconsistent metrics toward a unified, enterprise view of performance. In the near term, the role will prioritize establishing clarity and alignment on key business metrics and processes, particularly in a complex multi-ERP environment. Longer term, the role will drive data governance, business adoption of analytics, and the development of scalable data products that enable operational transparency, performance improvement, and AI readiness. The leader will also champion business-focused data science solutions—such as forecasting, scenario modeling, and optimization—to improve planning, identify performance drivers, and enable more proactive decision-making. This role requires a leader who is both: A strategic thinker capable of defining enterprise data frameworks A pragmatic operator who can work across functions to deliver tangible business outcomes quickly

Requirements

12–15+ years of experience in Business Analytics, Finance, Supply Chain, Operations, or Data Strategy roles
Strong understanding of end-to-end business processes in a manufacturing environment
Proven experience defining KPIs, business rules, and performance metrics
Demonstrated ability to bridge business and technical teams
Experience working in multi-ERP environments (SAP, Oracle, Dynamics, etc.)
Experience applying data science approaches (forecasting, statistical analysis, experimentation, optimization) to deliver business outcomes, with the ability to communicate assumptions and results to non-technical stakeholders
Strong communication skills with the ability to translate data into business insights for executives
Experience driving cross-functional alignment and organizational change
Solid understanding of data and analytics concepts (data modeling, BI tools, data warehousing), without being purely technical

Nice To Haves

Experience in data governance, data strategy, or enterprise transformation initiatives
Background in Finance, Supply Chain, or Commercial operations
Familiarity with Power BI, Tableau, or similar tools
Experience with data catalog, glossary, or governance tools (e.g., Purview)
MBA or equivalent business experience

Responsibilities

Enterprise Data Strategy & Business Alignment Define and own Alkegen’s enterprise data strategy from a business perspective, aligning data initiatives to business priorities and value.
Partner with business leaders to understand and document end-to-end processes (Order-to-Cash, Procure-to-Pay, Manufacturing, Record-to-Report).
Establish enterprise-wide KPI definitions, business rules, and semantic consistency across functions.
Identify and prioritize high-value analytics use cases aligned to business outcomes (margin improvement, operational efficiency, customer performance).
Data Governance, Ownership & Standards Establish and operationalize data ownership by business domain (Finance, Supply Chain, Commercial, etc.).
Define and implement business data governance frameworks, including: Business glossary and definitions KPI standardization Data stewardship model
Partner with IT and business stakeholders to embed governance into processes, not just tools.
Drive alignment on “one version of the truth” across business units.
Business Process & Data Integration Alignment Map business processes to systems and data flows, particularly across a multi-ERP environment.
Identify gaps between process execution and data availability/quality.
Work with IT/Data Engineering to ensure data models reflect true business processes and definitions.
Support the development of canonical data models and domain-based data structures.
Analytics Demand Management & Value Realization Establish a structured approach to intake, prioritization, and delivery of analytics requests.
Shift the organization from reactive reporting to value-driven analytics.
Define and track business value realization from analytics initiatives.
Ensure analytics solutions are adopted and used effectively by the business.
Data Science–Driven Business Solutions Partner with Finance & Commercial leaders to frame pricing and margin questions (price realization, discount effectiveness, customer/product profitability, margin leakage) and define the data needed to answer them consistently.
Develop & oversee business-friendly predictive and prescriptive analytics focused on pricing and margin (e.g., price-volume-mix and margin bridge drivers, discounting patterns, margin leakage/root-cause analysis, price sensitivity and elasticity, and deal guidance/guardrails).
Translate analytic outputs into clear pricing actions—recommendations, scenarios, and trade-offs—embedded into commercial operating cadence (pricing guardrails, approval workflows, quote/deal review, and playbooks).
Establish simple, repeatable measurements to validate impact (e.g., margin lift, leakage reduction, improved price realization, win-rate impact, and forecast accuracy) and prevent “one-off” analyses.
Ensure solutions align to governance and adoption standards (trusted data, documented assumptions, appropriate controls) and can be scaled into reusable data products.
Cross-Functional Collaboration & Change Management Act as the primary bridge between business leaders and IT/Data teams.
Drive enterprise alignment on data definitions, KPIs, and reporting standards.
Lead communication, training, and change management to reduce reliance on manual reporting and spreadsheets.
Influence leadership to adopt standardized, governed data sources & analytics tools.
Partnership with Technical Data Leadership Work closely with the Director of Data & Analytics (technical) to: Translate business needs into data and platform requirements Ensure data architecture supports business semantics and usability Maintain clear separation of responsibilities: This role: Business data, definitions, adoption, value Technical team: Platforms, pipelines, engineering