Director, Data Engineering

Marriott Vacations Worldwide

About The Position

The Director of Data Engineering is accountable and responsible for transforming data capabilities into trusted, scalable, and product‑oriented assets that enable analytics, AI, and business decision‑making. The role balances strategic vision, hands‑on execution, and leadership, driving measurable improvements in data quality, accessibility, cost efficiency, and business value realization. This role leads the modernization and adoption of data architecture, platforms, and operating models within assigned business domains, ensuring alignment with enterprise data strategy, governance standards, and business priorities. Acting as the senior data engineering leader for data consumption of one or more domains, the Director partners closely with domain executives, product owners, analytics teams, and technology leaders to deliver high‑quality, well‑governed, and reusable data products.

Requirements

At least 10 years of progressive experience in data engineering and data architecture.
At least seven years designing and delivering data platforms, pipelines, and curated analytical datasets at enterprise scale.
At least three years driving modernization, i.e., cloud migration, legacy warehouse refactors, data lakehouse adoption, streaming enablement, or data product implementation.
Proven delivery ownership for multiple concurrent initiatives spanning: ingestion → transformation → semantic modeling → consumption (BI/AI) governance, quality, security, and cost management
Experience partnering with domain executives to prioritize data investments, define measurable outcomes and drive adoption.
Modern Data Engineering & Architecture: Expert in designing and delivering scalable, cloud‑based data platforms, e.g., lakehouse, streaming, APIs, supporting analytics and AI at enterprise scale.
Data Product Leadership: Strong data‑as‑a‑product mindset with proven ability to deliver trusted, reusable datasets and data products aligned to business outcomes.
Data Quality & Governance: Deep experience embedding data quality, metadata, lineage, and stewardship practices to enable trusted reporting and advanced analytics.
Business Partnership: Trusted advisor to domain and executive leaders; skilled at translating business needs into prioritized data initiatives with measurable value.
Delivery & Execution: Proven leader of complex, multi‑initiative data modernization programs using agile and product‑based delivery models.
Enterprise Influence: Effective collaborator in matrixed environments, influencing standards, tooling, and operating models without direct authority.
Risk, Security & Cost Awareness: Strong working knowledge of data privacy, security, regulatory requirements, and platform cost optimization.

Nice To Haves

Master’s degree, e.g., MS Data Science/Analytics, MS Information Systems, or similar preferred.
Experience in data mesh concepts and data leadership preferred.
Experience in a matrixed environment with shared platform teams + data delivery teams preferred.

Responsibilities

Data Strategy & Roadmap: Acts as a key contributor to a multi-year data modernization roadmap for assigned domains, aligned to enterprise data, analytics, and AI strategies. Translates business objectives into prioritized data initiatives, investments, and measurable outcomes.
Data Product & Architecture Leadership: Leads design and delivery of data products, e.g., curated datasets, analytical models, APIs, using modern architectures such as data mesh, cloud platforms, and streaming where appropriate. Ensures data solutions adhere to enterprise standards for interoperability, security, scalability, and cost efficiency.
Data Quality, Governance & Trust: Establishes and enforces data quality, metadata, lineage, and stewardship practices in partnership with enterprise data governance teams. Drives accountability for data accuracy, completeness, and timeliness, enabling trusted reporting and advanced analytics.
Business Partnership & Value Realization: Serves as primary data modernization partner to domain business leaders, ensuring data initiatives directly support operational performance, financial outcomes, and strategic decision making. Quantifies and communicates business value delivered through data modernization, e.g., efficiency gains, risk reduction, revenue enablement.
Delivery Execution & Modern Engineering Practices: Manages end-to-end delivery of data modernization initiatives using agile and product-based delivery models. Removes delivery impediments, manages dependencies, and ensures timely, high-quality outcomes across multiple concurrent initiatives.
Enterprise Alignment & Collaboration: Actively collaborates with peer domain data leaders, central platform teams, and enterprise architecture to ensure consistency, reuse, and shared learning across data domains. Contributes to enterprise-wide data standards, tooling decisions, and operating model evolution.
Risk, Compliance & Operational Excellence: Ensures data solutions comply with regulatory, privacy, and security requirements. Proactively manages data risks, technical debt, and platform costs while improving resilience and operational stability.

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