Data Architect

Required Skills & Experience (Must Have) 12+ years of overall IT experience, with significant experience in enterprise data architecture, data engineering architecture or analytics platform architecture. Strong experience designing and implementing enterprise data and analytics architectures on Databricks. Strong understanding and practical experience with: Databricks Lakehouse architecture. Medallion Architecture (Bronze, Silver and Gold) or equivalent data-layering patterns. Databricks Unity Catalog. Data governance, metadata management and data lineage. Experience defining canonical data schemas, data models and source-system onboarding patterns. Strong understanding of enterprise data integration and experience designing integration patterns across: Git platforms. Azure DevOps. CI/CD pipelines and engineering toolchains. Ability to define architectural boundaries between data platform transformations and downstream analytics/reporting tools. Experience producing enterprise reference architectures, solution architecture documents and technical design recommendations. Experience preparing architecture documentation and technical inputs for security architecture reviews. Strong understanding of enterprise data governance, access control, data security and integration considerations. Proven ability to provide technical leadership and architectural guidance to engineering teams without requiring direct people-management responsibilities. Strong communication and stakeholder management skills. Strongly Preferred Skills & Experience Experience with process mining or object-centric data modelling. Hands-on experience with Celonis or Bloomfilter. Understanding of zero-copy or federated query patterns between a lakehouse and an analytics platform. Awareness of Microsoft Fabric and its integration with enterprise lakehouse architectures. Experience designing Power BI semantic models and enterprise analytics consumption layers. Experience with persona-based or tiered dashboard architecture for different stakeholder groups. Previous experience in developer productivity analytics, engineering intelligence or software engineering analytics. Understanding of engineering metrics and data from Git, Azure DevOps, CI/CD and related development platforms.