Data Products and Solution Strategy Expert

Purpose and Scope :

Astellas is seeking a strategic, results-driven data solutions expert to drive the enterprise adoption of modern data principles – including data mesh, domain-driven architecture, and data products - on the Databricks cloud platform. This role ensures alignment of data initiatives with business priorities, fosters cross-functional collaboration, and delivers measurable business value through advanced data capabilities.

The Data Products & Solution Strategy (DPSS) Expert is a global, cross-functional role responsible for the adoption, business-technical leadership, operational management, and continuous evolution of Astellas’ Internal Data Marketplace hosted on Databricks, with a primary focus on data products, advanced analytics, and AI-enabled solutions supporting the VALUE Delivery (Commercial and Medical Affairs) organization.

This role sits at the intersection of advanced data technologies and business value realization. The DPSS Expert is accountable for ensuring that data products and analytical solutions are technically robust, scalable, discoverable, business-ready and trusted, while partnering closely with Commercial and Medical stakeholders, Digital Excellence (IT), and other VALUE verticals (e.g. Finance, Legal, Procurement, R&D, etc.) to translate strategic priorities into high-impact data capabilities.

The DPSS Expert combines technical acumen with strong cross functional business partnership serving as a bridge between enterprise data strategy and business execution. This is crucial to ensure the Data Marketplace and Data Products/Solutions’ strong adoption, prioritization, measurable and consistent value delivery.

Responsibilities and Accountabilities:

VALUE Delivery Enablement and Chapter Strategy

Function as a key change agent for the Data Products & Solution Strategy Chapter within the Data Strategy Practice, translating chapter priorities into actionable initiatives.

Partner closely with the Chapter Lead, Data Products & Solution Strategy to Execute the chapter roadmap, scope, and operating model.

Represent the chapter in cross functional forums and initiatives as delegated.

Help oversee a portfolio of Commercial and Medical Affairs data products and analytical solutions. Ensure these are aligned to business workflows and deliver measurable impact.

Support change management efforts to embed data-as-a-product thinking and advanced analytics adoption across VALUE Delivery and also in other VALUE verticals (VALUE Creation, VALUE Enablement).

Data Products, Data Marketplace, Platforms & Advanced Analytics

Contribute to the development and refinement of standards, methodologies, and best practices related to data products, analytics, and AI enabled solutions.

Participate in the design, delivery, and lifecycle management of data products and analytical solutions aligned to Commercial and Medical Affairs needs.

Provide solid engagement and influence across:

o Databricks Lakehouse, including Delta, Unity Catalog, Databricks SQL, Workflows, and Databricks One

o Modern data lake and Lakehouse architecture

o Advanced analytics, feature engineering, and semantic modeling

o AI/ML and Generative AI–enabled analytics and applications

Ensure solutions are production ready, scalable, secure, and performant, while remaining discoverable and reusable through the Internal Data Marketplace.

Partner with Digital Excellence and platforms/data product engineering teams to align on:

o Architecture standards and patterns

o Platform tooling and integration approaches

o Reusable components and accelerators

Drive adoption of the Data Marketplace through enablement, demos, working sessions, and feedback loops with end users.

Guide teams to always incorporate business objectives especially through complex technical discussions and decisions - balancing speed, innovation, maintainability, and compliance.

Execution, Governance, and Agile Ways of Working

As an active member of the Data Products & Mesh Value Team within Customer Engagement Solutions Hub, engage in the quarterly planning cycles (QPC) and demand management for data products/solutions and Marketplace initiatives.

Lead delivery of marketplace, domains, and data product initiatives using Agile delivery practices, collaborating with cross-functional product, engineering, and analytics teams ensuring timely delivery and stakeholder alignment.

Utilize tools such as Azure DevOps (ADO) to manage backlogs, sprints, and cross-functional workstreams.

Support change management efforts to drive cultural adoption of data mesh, domain-driven thinking, and AI-enhanced data products.

Contribute to and enforce data product lifecycle standards, including documentation, quality SLAs, and usage metrics.

Define and track KPIs for marketplace adoption, reuse, reliability, and business impact.

Business Partnership & Stakeholder Engagement

Serve as a trusted partner to business, analytics, domain/data products stakeholders, global/regional and brand teams across VALUE Delivery.

Translate business questions and strategic priorities into well-defined, technically executable data product and solution designs.

Promote reuse and consistency through shared data assets, common definitions, and aligned solution patterns.

Support demand intake and prioritization for VALUE Delivery–focused data initiatives, balancing business value with platform capacity and architectural integrity.

Foster strong collaboration between business stakeholders, DX, and external partners to ensure alignment, transparency, and shared accountability.

Support stakeholder enablement and adoption through working sessions, demos, and ongoing feedback.

Consistently deliver clear communications to stakeholders at all levels, articulating the value and impact of data and AI initiatives.

Job Competencies and Knowledge:

Required Qualifications

Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, or a related discipline.

8 to 12+ years of experience in advanced data engineering, analytics, or data platform roles, with increasing scope and complexity.

Deep hands-on experience with Databricks and modern cloud-based data platforms (Lakehouse or equivalent).

Strong expertise in:

o Modern data lake / lakehouse architectures

o Data product design and lifecycle management

o Advanced business analytics and semantic modeling

o AI/ML and Generative AI concepts and applications

Demonstrated ability to operate effectively in a global, matrixed organization and collaborate across business and technical functions.

Strong communication skills with the ability to influence without authority.

Preferred Qualifications

Master’s degree in Data Science, Computer Science, AI, or a related STEM discipline.

Experience supporting Commercial, Medical Affairs, or customer-facing analytics in pharma or other highly regulated industries.

Databricks, cloud platform, or AI/ML certifications.

Familiarity with Agile delivery tools (ADO, Jira) and product-oriented operating models.

Experience with tools such as Qlik, Tableau, or similar BI platforms.