Databricks Partner
Modernize data without losing control.
Archetype Core designs governed Databricks architectures for organizations where security, lineage, reliability, and auditability matter.
Verified Databricks Credentials
Professional certification and Databricks partner training support Archetype Core’s work across data engineering, lakehouse architecture, governance, and migration.
Capabilities
Assess existing workloads, design governed Bronze, Silver, and Gold target architectures, modernize pipelines, and validate migrated results for reliable analytics, reporting, and downstream AI.
Production data pipelines using Delta Lake, PySpark, Databricks SQL, and Lakeflow, with an emphasis on reliability, maintainability, and operational visibility.
Unity Catalog architecture, governed tags, RBAC and ABAC, row filters and column masks, lineage, audit through system tables, external locations, storage credentials, and Hive metastore migration.
Governed data infrastructure designed to support enterprise analytics, machine learning, retrieval-based AI, and other production AI workloads.
Why Governance Matters
Modernization is not only about moving data faster. In regulated environments, organizations also need to understand where data came from, who can access it, how it changed, and whether downstream decisions can be traced back to reliable sources.
Archetype Core approaches Databricks architecture with governance, lineage, reliability, and auditability built into the foundation rather than added after deployment.
Whether you are establishing Databricks, modernizing legacy workloads, or strengthening governance around a growing lakehouse, Archetype Core can help design the architecture, migration path, validation approach, and implementation boundary. Review the reference systems and our Databricks governance analysis.
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