(Senior) Data Modeler / Data Architect

Boehringer Ingelheim is seeking a Data Modeler or Data Architect to join our Data Operations Team. This role is responsible for designing, governing, and evolving scalable, reusable, and production-grade data models within the team. These models serve as foundational assets for advanced analytics, AI, and business-critical decision-making across the pharmaceutical value chain. The Data Modeler will lead the end-to-end design and implementation of data models using industry-standard data-modelling techniques, i.e., Data Vault 2.0, Inmon, or Kimball, while ensuring seamless orchestration and deployment through dbt, Snowflake, Apache Airflow, and Jenkins. The role will be instrumental in driving performance optimization, cost efficiency, and operational excellence across our cloud data ecosystem. This role requires a strong, hands-on understanding of business needs and a technical understanding of data modeling, ELT/ETL processes, and data-warehousing principles, especially around Information Modeling and Data Vault 2.0, to derive models that fit business use cases. While you won't be coding every day, you must be capable of diving into code, reviewing designs, and resolving technical roadblocks alongside your team., * Develop scalable data models: design and deploy robust models to support interoperability, traceability, and analytics across domains, based on modeling best practices and continuous enhancements.

• Ensure standards and governance: align models with internal and industry-wide standards, collaborating with governance teams to ensure quality and compliance.
• Collaborate with stakeholders: translate business requirements into effective data structures and influence data-strategy decisions.
• Drive innovation: adopt modern data-modeling approaches, foster innovation, and promote efficiency within the team.
• Quality assurance: establish processes to validate model integrity, ensure auditability, and manage lifecycle updates.

For this role, we are explicitly not looking for a Data Scientist; our ideal candidate would come from a TA or regions business background with a strong technical understanding., * 2+ years in data modeling, data strategy, or enterprise data-warehousing in the pharmaceutical or regulated industries. Proficiency in relational, dimensional, and semantic modeling methodologies, with hands-on experience using modeling tools such as Innovator, SqlDBM, or Erwin.

• Additional for Senior role: 5+ years in data modeling or data architecture, plus hands-on project-management experience.
• Able to perform in a high-performance culture.
• Strong communication, problem-solving, and stakeholder-management skills, with a focus on scalability and long-term impact.
• Strong proficiency in SQL, with hands-on experience building and maintaining dbt models (e.g., stored in Snowflake) for large-scale data transformations.
• Experience working within Git-based development workflows, CI/CD practices, and Jira-based sprint planning and backlog management.
• Deep understanding of regulatory requirements, data-governance practices, and industry trends.
• Strong communication skills in spoken and written English