Lead Data Architect

Qualifications and Competencies

Required:

• Bachelor’s Degree in computer science, information science, knowledge engineering, computational linguistics, data engineering, information technology, or a related field
• 5+ years of experience in data architecture, or a similar role, with proven leadership in designing and delivering production-grade data pipelines and services
• Strong ownership of deliverables, high standards for code review and peer mentorship, and a commitment to clear documentation, metadata/lineage publishing, and sustainable data engineering standards and practices
• Proficiency in designing and implementing data models (conceptual, logical, and physical)
• Proficiency with Databricks, including DBX Asset Bundles, Lakeflow Jobs, Unity Catalog, Access control and governance model and Databricks CLI
• Extensive experience with API design patterns and Ability to integrate data from source systems using various interface patterns, such as OpenSharing/Delta Sharing, Iceberg-Sharing, ODBC, GraphQL, OData, REST, or event streaming
• Strong engineering skills (data engineering, software engineering, or cloud engineering)
• Proficiency in Python programming, especially PySpark and Kapitan
• Proficiency in Git, including Github Actions, CI/CD Pipelines (declarative YAML), Branching strategies, and trunk-based development
• Hands-on experience with Infrastructure-as-code, ideally Terraform on AWS
• In-depth knowledge of FAIR Data Principles, Linked Data principles, and Data Mesh architecture concepts, with demonstrated ability to apply them in practice
• Proficiency with data governance and security principles and practices
• Strong analytical and communication skills
• Good communication and collaboration abilities to work independently in a self-organized team
• High level of accuracy and attention to detail

Preferred

• Experience with GxP validation and Computerized Systems Validation
• Experience in Requirements Engineering
• Experience with semantic layer concepts in modern data platforms such as Databricks, Snowflake, or Microsoft Fabric
• Experience designing and implementing Model Context Protocol (MCP) servers
• Hands-on experience with GraphRAG solution design and implementation
• Knowledge of data privacy regulations (e.g., GDPR, CCPA)
• Cloud engineering experience (e.g. AWS, Azure)
• Knowledge in the pharmaceutical domain (e.g. LOINC, SNOMED CT, omics, targets, assays, clinical studies, RWE, etc.)