Data Products and Solution Strategy Expert

About Astellas

Astellas is a global life sciences company committed to turning innovative science into VALUE for patients. We provide transformative therapies in disease areas that include oncology, ophthalmology, urology, immunology and women's health. Through our research and development programs, we are pioneering new healthcare solutions for diseases with high unmet medical need. Learn more at Astellas.com.

Are you driven to make a real difference in the lives of patients?

We're seeking passionate individuals who thrive in dynamic environments, embrace new ideas, and aren't afraid to take intelligent risks. People who act with unwavering integrity and are deeply committed to making a tangible impact.

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 senior individual‑contributor and solution‑delivery role within the Data Products & Solution Strategy Chapter. This is a global, cross-functional role responsible for the hands‑on design, delivery, and adoption of data products, analytics, and AI‑enabled solutions, primarily supporting VALUE Delivery across Commercial and Medical Affairs.

Reporting to the Chapter Lead, Data Products & Solution Strategy, the DPSS Expert focuses on execution excellence, translating defined data product strategies and priorities into production‑ready, business‑consumable solutions hosted on Databricks via the business-facing internal Data Marketplace platform. The role operates at the intersection of advanced data technologies and business needs, ensuring solutions are technically robust, reusable, discoverable, and aligned to business workflows across VALUE Delivery while also effectively collaborating with other VALUE verticals (VALUE Creation/R&D and VALUE Enablement functional areas such as DigitalExcellence/IT, Procurement, Finance, etc.)

The role is predominantly business delivery‑oriented combined with technical acumen in advanced data offerings, with meaningful engagement with business and analytics stakeholders to support adoption and impact.

Responsibilities and Accountabilities:

VALUE Delivery Enablement and Chapter Strategy

Support the scope and operational activities of 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.

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

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

Ensure outputs are actionable, interpretable, and aligned to how business teams work.

Support enablement activities including demos, walkthroughs, and documentation.

Data Products & Solutions Delivery

Deliver sound business and functional requirements to support the design, build, and implementation of data products and analytical solutions aligned to Commercial and Medical Affairs use cases.

To ensure business roadmap is consistently carried out, influence across the implementation and evolution of:

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

Modern data lake and lakehouse architecture

Advanced analytics, feature engineering, and semantic modeling

AI/ML and Generative AI-enabled analytics and applications

Ensure solutions are production‑ready, performant, secure, and scalable, while fitting within established platform and architecture standards.

Apply defined data product standards, patterns, and lifecycle practices.

Assist in troubleshooting and resolving business and technical issues across data pipelines, analytics layers, and AI solutions.

Data Marketplace & Platform Enablement

Actively support the adoption and effective use of the Internal Data Marketplace by analytics teams and business users.

Support publishing and maintenance of data products/assets within the Internal Data Marketplace, ensuring proper documentation, metadata, and usability.

Partner with platform, data engineering, and Digital Excellence teams to:

Implement reusable components and accelerators

Align with tooling, integration, and security requirements

Improve performance and reliability of data assets

Participate in continuous improvement of data marketplace capabilities and user experience.

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.

Execute data product and analytics work using Agile delivery practices, contributing to sprint planning, backlog refinement, and delivery execution.

Actively use tools such as Azure DevOps (ADO) to manage work items and dependencies.

Adhere to data governance expectations, including Data quality and validation, Lineage and documentation, and Access and security controls.

Contribute to tracking delivery metrics such as usage, performance, and solution reliability.

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

Collaboration and Stakeholder Management

Work closely with VALUE Delivery stakeholders, DX/IT, other functional areas (e.g. Finance, Legal, Procurement, etc.), and external partners.

Communicate technical topics clearly to non‑technical audiences when required.

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

Provide clear status updates and surface risks or dependencies early.

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

Job Competencies and Knowledge:

Required Qualifications

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

6-10+ years of experience in advanced data engineering, analytics, or data platform roles.

Hands‑on experience with Databricks and modern cloud data platforms.

Solid expertise in:

Modern data lake / lakehouse architectures

Data modeling and analytics development

Advanced analytics and AI/ML concepts, including Generative AI

Strong communication skills with the ability to influence without authority.

Experience working in cross‑functional, matrixed teams.