Role Overview

The Head of Data & Analytics Engineering (Senior Director) is an entrepreneurial and visionary engineering leader who will build and scale our Data & Analytics team. You will be responsible for building our data + Generative BI strategy, governance, and delivery across the organization while aligning them with the organization’s strategic goals.

A core focus of the role is improving data delivery velocity and reliability at scale. You will identify systemic bottlenecks across ingestion, modeling, access, governance, and consumption, and drive structural improvements that reduce time-to-insight while maintaining high standards for quality, security, and compliance. This includes setting clear delivery expectations, success metrics, and service levels for data products.

Key Responsibilities

Set Data Platform Strategy & Direction

• Define and execute a multi-year strategy for data and analytics platforms aligned with business priorities and AI roadmaps

• Establish clear architectural principles across centralized platforms and domain-owned data products

• Drive the company’s evolution toward a federated or data mesh operating model, balancing domain autonomy with platform-enforced standards

• Advanced the integration of Generative AI into data platforms to enable self-service and accelerate insight

Build & Operate Scalable Data Platforms

• Own the design and operation of enterprise data platforms supporting analytics, reporting, machine learning, and Generative AI applications

• Build unstructured vector store and RAG capabilities to power Generative AI applications

• Define platform capabilities that enable domains to publish, manage, and operate high-quality data products

• Ensure platforms are reliable, secure, cost-effective, and scalable

Own Data Delivery & Business Outcomes

• Own end-to-end data delivery for analytics, reporting, and AI use cases, from intake and prioritization through production delivery

• Establish operating models that balance central platform capabilities with domain-led data product delivery

• Ensure data products are delivered with clear ownership, quality expectations, and measurable business impact

• Drive improvements in data delivery speed, reliability, and predictability, reducing time from request to usable insight

• Partner with business and analytics leaders to define success metrics and ensure data delivery aligns to strategic priorities

Integrate Generative AI for Data & Analytics

• Lead the application of Generative AI within data and analytics platforms to improve usability and adoption

• Enable capabilities such as natural language data discovery, intelligent metadata and documentation, and guided analytics

• Partner with AI/ML leadership to ensure GenAI capabilities are reliable, governed, and production-ready

Enable Trusted, Self-Service Data

• Establish platform-level standards for data quality, lineage, metadata, and observability

• Ensure governance, security, and compliance are embedded by design and appropriate for regulated environments

• Reduce time-to-insight by enabling intuitive discovery, consistent metrics, and clear data contracts

Lead & Scale the Organization

• Build, mentor, and lead a high-performing organization of data platform and analytics engineering leaders

• Establish clear operating models, accountability, and delivery cadence across teams

• Foster strong cross-functional partnerships with application engineering, AI/ML, product, and business leadership

Qualifications

Required:

• 15+ years of experience in data engineering, analytics platforms, or related technical domains

• 5+ years leading and scaling data engineering or data platform organizations

• Proven experience applying Generative AI and LLM’s to data platforms or data products

• Proven experience building unstructured vector stores and RAG solutions

• Proven experience designing and operating data mesh architectures and domain-oriented data platforms

• Strong understanding of modern cloud data platforms and analytics ecosystems

• Demonstrated experience enabling self-service analytics at enterprise scale

• Experience operating in regulated environments with strong governance and compliance requirements

• Exceptional communication and cross-functional collaboration skills.

• Excellent stakeholder engagement, prioritization, and communication skills.

Preferred:

• Advanced degree (MS/PhD) in Computer Science, AI/ML, engineering or related field.

• Experience in healthcare, pharma, diagnostics, or other regulated industries.

• Familiarity with AI governance frameworks, bias detection, explainability, and compliance (e.g., HIPAA, CLIA, FDA).