Research Data Engineer

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 (https://www.astellas.com/en)

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:

We are seeking an experienced Research Data Engineer to design, deliver, evolve, and operate domain-specific data solutions, integrations, and reusable, governed research data products across the R&D technology landscape. The role applies fit-for-purpose technologies—including Databricks where appropriate—to meet Research & Discovery, translational science, analytics, reporting, AI, and scientific decision-making needs. Success is measured by trusted solutions with clear ownership, data contracts, quality expectations, metadata, service levels, and reusable consumption patterns.

Working with Research scientists and stakeholders, Data Product Owners, Domain Data Architects, Domain Data Modelers, Data Governance Specialists, Data Scientists, and Platform Engineers, this role translates prioritized scientific and business outcomes into production-ready data solutions and products. The role collaborates with Platform Engineers responsible for shared platform capabilities, standards, and enablement.

Responsibilities and Accountabilities:

• Design, build, test, deploy, maintain, and support reliable data pipelines, integrations, curated datasets, and reusable research data products from discovery through production.
• Partner with Data Product Owners, Research stakeholders, application teams, and architects to translate roadmaps, requirements, and acceptance criteria into incremental engineering deliverables and production releases.
• Develop fit-for-purpose data solutions across the R&D technology landscape using Databricks, KNIME and other appropriate database, integration, orchestration, and processing technologies.
• Integrate structured, semi-structured, and unstructured data from research, laboratory, scientific application, and external-provider systems to support scientific workflows, analytics, AI, and reusable data products.
• Transform scientific data into standardized and contextualized datasets while preserving provenance, experimental context, metadata, quality, and traceability.
• Translate approved data designs and scientific requirements into scalable technical data models and implementation patterns.
• Collaborate with Data Governance and Quality stakeholders to embed data ownership, quality, lineage, metadata, security, privacy, retention, validation, and other applicable compliance requirements using appropriate governance technologies, including Unity Catalog where applicable.
• Design and implement fit-for-purpose data interfaces and consumption patterns, including governed tables and views, APIs, semantic models, feature datasets, vector indexes, knowledge-graph assets, and agent-ready datasets, with appropriate versioning and backward compatibility.
• Support appropriate testing, data-quality controls, monitoring, and operational processes to help ensure reliable and trusted data solutions.
• Apply DevOps practices, including source-code management, CI/CD, automated testing, peer review, environment promotion, controlled releases, and reusable engineering standards, templates, components, and accelerators.
• Optimize SQL and Spark workloads, databases, integrations, compute, storage, and workflows for performance, reliability, scalability, resilience, and cost efficiency.
• Work in Agile delivery teams, contributing to backlog refinement, sprint planning, demonstrations, retrospectives, release planning, operational readiness, and measurable scientific and business outcomes.

Required Qualifications:

• Bachelor's or master's degree in Computer Science, Data Engineering, Health Informatics, Bioinformatics, Life Sciences, or a related technical discipline.
• Seven or more years of experience building and supporting enterprise-scale data pipelines, curated datasets, and reusable data products on cloud data platforms.
• Strong SQL and Python skills, with experience in ETL/ELT, orchestration, distributed processing, data warehousing, dimensional/canonical modelling, schema design, and API or interface development.
• Hands-on experience designing and supporting data integrations using REST APIs, relational and non-relational database connectivity, flat-file transfers, SFTP, cloud storage and managed integration services, and structured or semi-structured formats such as JSON, XML, CSV, and Parquet.
• Experience with Databricks, Apache Spark, Delta Lake, or comparable technologies and with production-grade data product operations
• Experience implementing data contracts, quality controls, metadata, lineage, documentation, automated testing, Git-based development, CI/CD, monitoring, and schema evolution.
• Strong troubleshooting, performance-tuning, communication, and cross-functional collaboration skills.
• Experience working in Agile, product-oriented delivery environments with backlog-driven incremental releases.

Preferred Qualifications:

• Experience supporting pharmaceutical or biotechnology Research & Discovery.
• Familiarity with ELNs, LIMS, registration systems, assay platforms, laboratory instrumentation, and scientific data providers.
• Experience with Unity Catalog, dbt, KNIME or comparable transformation tooling, MLflow, vector search, semantic models, knowledge graphs, or generative AI.
• Familiarity with FAIR data principles, scientific ontologies, controlled vocabularies, metadata management, and regulated scientific environments.

Working Environment

• Hybrid work arrangements (on-site/work from home) from certain locations may be permitted in accordance with Astellas' Responsible Flexibility Guidelines. The role may require collaboration across global time zones and limited international travel.

What awaits you at Astellas?

Global collaboration: Become part of a connected global business of like-minded life science leaders, all dedicated to improving patients' lives worldwide.

Real-world patient impact: Contribute to transformative therapies that reach patients around the world, knowing your work makes a difference every day.

Relentless Innovation: Join a company at the forefront of scientific breakthroughs, where you'll have the opportunity to shape the future of healthcare.

A Culture of Growth: Chart your own course within a supportive environment that values your contributions, champions your development, and empowers you to pursue your passions.

Our Organizational Values and Behaviors

Values: Innovation, Integrity and Impact sit at the heart of what we do.

Behaviors: We come together as ‘One Astellas, working with courage and a sense of urgency . We are outcome focused and consistently take accountability for our personal contribution.

"Beware of recruitment scams impersonating Astellas recruiters or representatives. Authentic communication will only originate from an official Astellas LinkedIn profile or a verified company email address. If you encounter a fake profile or anything suspicious, report it promptly to LinkedIn's support team through LinkedIn Help”