Product Manager Data Modeler - Data Integration & Processing, PDM Digital

Nasze wymagania:
Required Qualifications:
Bachelor’s or higher degree in Computer Science, Information Systems, or a related field.
Relevant industry certifications (e.g., Databricks, AWS/Azure, Agile) are highly preferred.
Prior experience in the pharmaceutical, biotech, or other highly regulated environments is highly desirable.
Extensive experience in data engineering, data architecture, and data platform delivery.
Proven track record in designing and implementing data platforms, ETL frameworks, and data integration solutions.
Experience working across multiple industries or complex domains, with strong adaptability to new environments.
Demonstrated leadership in end-to-end project delivery, including architecture, development, deployment, and production support.
Experience with data governance and regulatory compliance frameworks.
Technical Skills:
Cloud Platforms: Azure and AWS.
Data Platforms & ETL Tools: Databricks, IBM DataStage, Synapse, Talend, Infosphere.
Programming & Processing: Python, PySpark, SQL, PL/SQL, T-SQL.
Data Architecture & Modelling: Relational, Dimensional, Data Vault.
Integration Technologies: CDC (e.g., Fivetran SAAS, HVR), REST API’s, MQTT, AMQP (e.g., RabbitMQ), real-time data streaming platform (e.g. Kinesis, Kafka), IoT platform (e.g., AVEVA Connect).
Databases: MS SQL Server, Oracle, MySQL, cloud-based relational database services, cloudbased NoSQL database services.
Automation, DevOps & CI/CD: Azure DevOps (pipelines, repos), automated deployment, reusable data ingestion patterns, lifecycle management.
Data Governance: Data quality frameworks (e.g., Spark DQX), governance tools (e.g., Databricks Unity Catalog), data contracts, metadata management, and regulatory (e.g., GxP) compliance.
Soft Skills:
Strong ability to operate in complex business environments and translate requirements into data solutions/designs/architectures.
Excellent communication and stakeholder management abilities.
Ability to work independently and collaboratively across regions and time zones

Zakres obowiązków:
Purpose and Scope:
Design and govern domain-specific data architectures across Manufacturing, Clinical, Supply Chain, and CMC, ensuring scalable, secure, compliant, and reusable data solutions that meet current and future business needs.
Act as the key domain architecture partner to business and DigitalX teams, translating business requirements into industrialized data patterns and workflows while ensuring alignment with enterprise standards, GxP requirements, and emerging AI-related regulations.
Role and Responsibilities:
Define and govern domain-specific data architectures for Manufacturing, Clinical, Supply Chain, and CMC, ensuring alignment with enterprise architecture standards and business priorities.
Establish and govern domain architectural principles, ensuring alignment with enterprise data standards and strategies.
Translate business and data design requirements into scalable, fit-for-purpose ingestion patterns.
Oversee and review implementation delivered by central data engineering teams, ensuring compliance with architecture, quality, and governance standards.
Lead the design and delivery of end-to-end data workflows, covering ingestion, transformation, and integration across different data sources.
Collaborate with cross-functional teams (e.g., business stakeholders, DigitalX hubs, and QA) to deliver high-quality, scalable, and secure data solutions.
Provide architectural leadership and guidance on domain-relevant platform capabilities, including CI/CD, automation, and DevOps practices.
Ensure the validated state of all ingestion patterns, data workflows, and data artifacts (e.g., Delta tables, views, notebooks, and datasets).
Ensure all domain solutions and components are aligned with current requirements and scalable for future business needs, bridging business and technical teams.
Provide coaching, guidance, and subject matter expertise to data and platform engineering teams, supporting capability development and adoption of best practices.
Ensures patterns and workflows are transitioned to Operations ownership and governed under formal change control.
Drives continuous enhancement of architectures and workflows by leveraging emerging digital technologies and innovation opportunities.
Assess emerging technologies, architecture patterns, and regulatory requirements to continuously evolve domain data capabilities and standards.

Oferujemy:
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.
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.