MetLife

Director, Data & Analytics Delivery (Modeling, Data Science & Governance)

Location: Cary, NC; New York, NY; Tampa, FL
Reports to: VP – Data & Analytics (Corporate Functions)
Team: Leads a multi‑disciplinary team of ~10–15 comprising of data modelers, data scientists, data stewards, and analytics engineers.

This Director role leads the execution and delivery of enterprise‑grade data and analytics and data governance initiatives that enable trusted, high‑quality data, advanced analytics, and AI across Corporate Functions. The leader will collaborate with stakeholders from Finance, Actuarial, Reinsurance and Risk to drive measurable business outcomes through modeling and data science and institutionalize governance so that scalable data solutions are delivered.

What You’ll Do

1) Portfolio Leadership & Delivery

• Define and execute a delivery roadmap that aligns programs and projects with Corporate Functions objectives; create canonical models that align to Enterprise standards and enable functional stakeholders to institute adequate governance processes.
• Lead implementation of cloud‑native architectures (e.g., data mesh / lakehouse) and cost-effective data acquisition pipelines across structured and unstructured sources.
• Proactively manage team capacity and resource allocation, ensuring delivery commitments are met while fostering professional growth and maintaining a balanced workload.
• Serve as a primary point of contact for stakeholders, facilitating clear and timely communication to align expectations, gather requirements, and translate business needs into actionable data initiatives.
• Work with team and ART lead through requirements gathering process, collaborating with business and technology partners to define project scope, success criteria, and solution design.
• Assess and manage the budget, ensuring cost-effective operations and optimal use of resources to maximize value delivery.

2) Data Modeling Excellence

• Establish standards and guardrails for conceptual, logical, and physical modeling; champion domain‑driven design and evidence‑based modeling practices.
• Oversee modeling for analytics, APIs, and integration (e.g., dimensional 3NF/star/snowflake; schema design and optimization in SQL/NoSQL).
• Govern model lifecycle (versioning, lineage, usage) to ensure consumable, reusable data assets across CF domains.

3) Data Science Outcomes

• Partner with business leaders to frame problems, translate models into insights, and deliver measurable outcomes (e.g., cost, risk, efficiency).
• Build reusable feature stores and MLOps pipelines that operationalize analytics and support AI/LLM experimentation responsibly.

4) Data Governance by Design

• Establish and enforce policies, metadata management, lineage, and quality in partnership with the Data Governance Council and business stewards.
• Align delivery with privacy, security, and compliance standards; embed controls into pipelines and consumption layers.

5) People Leadership & Culture

• Hire, mentor, and develop a high‑performing team; promote a culture of innovation, agility, and continuous improvement.

What You’ll Bring

Core Qualifications

• Strategic vision aligning platform‑based architecture and modernization with AI enablement.
• Technical depth in Azure cloud‑native data platforms; lakehouse/data mesh; ingestion at scale (CDC, streaming, batch);
• Hands-on Data Governance program execution and Data Models development
• Proven leadership & influence across cross‑functional teams and senior stakeholders.
• Strong governance, privacy, and security acumen; quality frameworks and lineage.

Required Skills: 

Experience & Education

• 10+ years across data engineering/data modeling and governance; 3–5+ years leading cloud‑native modernization programs.
• 5+ years of experience with hiring, mentorship, and developing a high‑performing team; promote a culture of innovation, agility, and continuous improvement.
• Bachelor’s or master’s in computer science, Information Technology, or related field.

Tools & Technologies (examples)

• Azure experience including most of the following tool & technologies: Data Factory, Synapse, Databricks, Delta Lake, Spark—Scala/Python, Erwin, Visio, SQL, Cosmos DB, Power BI; Governance solutions (ex: Collibra, Atacama).

Preferred Skills:

• Experience in insurance or financial services; familiarity with GenAI/LLMs and their integration into data platforms.