Product Manager Data Modeler - Data Products & Self Service, PDM Digital

Nasze wymagania:
Essential Qualifications:
Prior experience in the pharmaceutical, biotech, or other highly regulated environments is highly desirable.
Extensive experience delivering enterprise-scale data and analytics solutions, specializing in the design and industrialization of domain-driven data products and governed self-service data ecosystems across complex environments.
Strong experience preparing and structuring data for self-service consumption, including development of curated data layers, standardized data models, and semantic definitions to ensure consistent data interpretation.
Strong experience in data quality and governance frameworks in regulated environments.
Demonstrated leadership in end-to-end delivery from requirements gathering and design to deployment and production support.
Experience working across multiple domains (e.g., manufacturing, supply chain) and translating business needs into scalable and consumable data solutions.
Technical Skills:
Data Product & Self-Service Ecosystems: Design and industrialization of domain-specific data products, data marketplaces, and governed self-service capabilities.
Cloud Platforms: Azure and AWS.
Data Platforms: Databricks, Synapse.
Programming & Processing: Python, PySpark, SQL, PL/SQL, T-SQL
Data Architecture & Modelling: Relational, Dimensional, Data Vault, semantic modelling.
Data Engineering & Integration: ETL/ELT frameworks, APIs, CDC tools, real-time streaming platforms.
Databases: MS SQL Server, Oracle, MySQL, cloud-based relational and NoSQL database services.
Automation, DevOps & CI/CD: Azure DevOps (pipelines, repos), automated deployment, reusable data product 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:
In this role, you will lead the design and governance of domain-specific data products and self-service ecosystem, enabling business teams to efficiently create, consume, and operationalize trusted. Ensure data products are standardized, scalable, compliant, and enriched with business context to support analytics, AI and digital use cases.
This position reports to the Lead Digital Strategy and Transformation (MONOzukuri Knowledge Management & genAI) and is based in Warsaw, Poland.
Role and Responsibilities:
Define and govern standards, design principles, and operating frameworks for domain data products and self-service capabilities.
Drive the scalable and standardized design of reusable data products (e.g., data models, APIs, digital twins, and AI-enabled solutions) through automation and reusable design patterns.
Ensure data is prepared for self-service consumption by embedding quality, governance, and context (semantic definitions, metadata, metrics, and ontologies) into the design.
Establish and govern data product and information architecture principles, ensuring alignment with enterprise standards and enabling scalable, interoperable solutions.
Oversee and review implementation delivered by central data engineering teams and data modelers, ensuring compliance with architecture, quality, and governance standards.
Ensure data products and self-service capabilities are production-ready and operationalized, including lifecycle management, monitoring, and supportability.
Collaborate with cross-functional teams (e.g., business stakeholders, DigitalX hubs, and QA) to deliver high-quality, scalable, and secure data products and self-service environments.
Ensure the validated state of GxP data products.
Partner with business stakeholders to identify opportunities for increased adoption, reuse, and value realization from data products and self-service capabilities.
Provide coaching, guidance, and subject matter expertise to data and platform engineering teams to support capability development and continuous improvement.
Ensure self-service environments, data models, and context are accessible to the business, and governed under formal change control.
Drive continuous enhancement of the self-service environment, data models, and context by leveraging emerging digital technologies and innovation opportunities.

Oferujemy:
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