Computer Science Engineer Jobs in Lafayette, IN (NOW HIRING)

About the Role:

The Director, Enterprise Data is responsible for building and leading the company's enterprise-wide data strategy to ensure data integrity, availability, and accessibility for advanced analytics and business decision-making. This role establishes the vision, roadmap, and governance required to transform data into a strategic business asset.

The Director leads cross-functional teams to define master data standards, data management processes, architecture frameworks, and data platform optimization. They will serve as a trusted advisor to senior leaders, enabling data-driven decisions through scalable solutions, high-quality data, and advanced capabilities in data engineering, reporting, analytics, and business intelligence.

Your Responsibilities:

Strategic Leadership

• Develop and execute the Enterprise Data strategy aligned to business priorities, digital modernization, and transformation initiatives.

• Lead the evolution of enterprise data architecture, platforms, and data pipelines to support business intelligence, predictive analytics, and AI/ML.

• Create and maintain the enterprise data roadmap including data platforms, governance frameworks, data quality, and integration architecture.

• Secure alignment with executive leadership, ensuring data initiatives directly enable growth, operational excellence, customer experience, and efficiency.

Data Governance & Quality

• Establish enterprise data standards, policies, data stewardship roles, and controls to ensure data is accurate, secure, and compliant.

• Lead enterprise-wide Master Data Management (MDM), metadata strategy, data privacy frameworks and data lifecycle management.

• Partner with Legal, IT Security, and Internal Audit on data protection, risk management, regulatory compliance, and controls.

• Implement data quality monitoring, remediation processes, and continuous improvement mechanisms.

Technology, Architecture & Analytics Enablement

• Oversee design and optimization of data platforms (warehouse, lake, lakehouse, and integration layers).

• Partner closely with IT, Cloud, ERP, and Digital Product and Software Engineering teams to modernize legacy systems and integrate complex data sources.

• Drive architectural decisions relating to integrations, APIs, interoperability, and future scalability.

• Enable self-service analytics through standardized datasets, governed models, and curated data products.

Leadership & Collaboration

• Lead a high-performing team of data engineers, data architects, data governance experts, MDM specialists, and Power BI analysts.

• Build and mature the enterprise data operating model, including service levels and intake, prioritization, security protocols, and delivery models.

• Influence enterprise stakeholders across Finance, Operations, HR, Supply Chain, Commercial, Product, IT, and external partners to ensure alignment and adoption.

• Communicate strategy, KPIs, risk, and progress to executive stakeholders, including Board updates when required.

Program & Project Execution

• Manage strategic initiatives including data platform modernization, integration strategies, MDM deployments, ERP/CRM transformations, cloud migration, and analytics enablement.

• Oversee vendor relationships related to data integration, cloud infrastructure, MDM platforms, AI, data warehousing, and BI tools.

• Develop business cases, ROI models, and investment plans to drive data capabilities and capacity.

Let's Talk About Your Qualifications:

• Bachelor's degree in Computer Science, Information Management, Data Science, Engineering, or related field required; Master's preferred.

• 10+ years in data strategy, data architecture, information management, or enterprise analytics leadership roles.

• Proven experience leading data modernization or enterprise data governance at scale (multi-site, multi-business-unit environment).

• Experience driving change in complex environments including ERP transformations, mergers, data consolidation, cloud migration, or large-scale integration programs.

• Expertise in enterprise data architecture, warehouse/lake design, integration and ETL/ELT frameworks, cloud environments, and structured/unstructured data solutions.

• Strong understanding of Azure, AWS, or GCP data technologies, DataBricks, MDM platforms, data cataloging, and BI/reporting tools.

• Knowledge of data privacy, cyber security, compliance regulations, and risk frameworks.

• Understanding of RPA, AI/ML enablement, data modeling, and algorithmic data structures (preferred).

• Strategic thought leadership with ability to translate data outcomes into business value.

• Strong executive presence and communication skills, able to influence at all levels.

• Track record of building, developing, and retaining high-performing technical and analytic teams.

• Ability to mobilize cross-functional stakeholders, resolve competing priorities, and drive adoption.

• Demonstrated decision-making, problem-solving, change leadership, and program management skills.

Leadership Attributes:

At Wabash, we pride ourselves on being empowering, and there are some things we feel very strongly about:

• Embrace Diversity and Inclusion - Solicit and respect the input of others, celebrate differences, and strive for transparency and inclusiveness

• Seek to Listen - Actively listen to reach the best solution and make the strongest decisions

• Always Learn - Strive to improve; do not quit or settle for the status quo

• Be Authentic - Demonstrate honesty, incredible energy, and grit in everything you do

• Win Together - Collaborate, seek alignment, and excel at cross-group communication to success as one team and One Wabash

Join us in turning ideas into world-changing realities. Curate and build your high-impact professional career at Wabash!

Affirmative Action/EEO Statement:

Wabash is committed to providing equal employment opportunity for its associates and applicants without regard to race, color, religion, sex, age, national origin, veteran status, disability, or other protected class or activity under federal, state, or local law. All employment decisions must be based on neutral, legitimate criteria. All employment policies and rules shall be applied equally to similarly situated associates.

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