Senior IT Architect II (Data Products Manager- Databricks architect)

The Staff Data Products Manager & Databricks Center of Excellence (CoE) Lead is a vital hybrid role. This leader is responsible for maximizing the business value derived from the enterprise data assets and ensuring the scalable, secure, and cost-efficient operation of the Databricks Lakehouse and Data Intelligence Platform.

This role will define, shape, and drive the future of data products development; from raw data collection to high-value AI insights; whilst establishing the governance frameworks, solution delivery, operational standards, and comprehensive organizational literacy programs required for enterprise-wide data excellence.

The role acts as the leader of the organization’s strategic data assets for Corporate functions and the platform operating model, generating efficiency gains via the CoE that unlocks velocity and speed-to-market for high-value, governed data products.

This position mandates the integration of two traditionally separate leadership roles, requiring deep systems thinking and a people-first approach to technical enablement.

Strategic Data Products Ownership (Vision & Value):
Define the long-term data products vision, detailed roadmap, and comprehensive corporate solutions development strategy for all data products and resulting AI insights. Own the full product lifecycle, from ideation and requirements definition to development, launch, and post-launch optimization. Act as the primary interface, collaborating with technical experts to translate complex technical capabilities into business use cases and balancing stakeholder expectations against existing development capacity and priority. Establish frameworks to set, track, and measure Key Performance Indicators (KPIs) throughout the data products lifecycle.

Databricks CoE Leadership & Governance (Scale & Security):

Design and launch the Databricks Center of Excellence (CoE). Establish and maintain the architectural governance framework, collaborating with data architecture to mandate standards such as Medallion Architecture and defining acceptable architectural patterns. Oversee the implementation and governance of Unity Catalog, defining best practices for administering identities, configuring security, managing compute resources, and securing data access within the Lakehouse. Define the Solution Qualification process for technical review audits and criteria that all new data products must meet before production deployment.

Platform Operations and MLOps:

Mandate and enforce operational excellence principles, including the use of Infrastructure as Code (IaC) for all environment deployments. Establish organizational standards for CI/CD implementation and Source Code Management (SCM). utilizing Databricks GitLab folders. Manage platform cost efficiency by establishing and enforcing policies for compute resource capacity, service limits, quotas, and utilization to measurably reduce execution costs (FinOps). Collaborate with AI governance to define the MLOps lifecycle to ensure AI models are managed, monitored, and continuously updated using tools like MLflow.

Organizational Enablement and Literacy:
Develop and execute scalable enablement programs that strengthen technical depth. Design and deploy a tiered Data Literacy Program tailored to various roles (executives, managers, technical teams). Drive internal credentialing, mandating certifications, such as the Databricks Accredited Platform Administrator.