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databricks-lakehouse-engineering-at-azure

Review and guide Databricks Lakehouse engineering on Azure: medallion architecture (bronze/silver/gold), Delta Lake pipelines, ADLS Gen2 access via Unity Catalog external locations and storage credentials, Access Connector managed identity, cluster access mode enforcement, AKV-ba

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Skill manifest

Databricks Lakehouse Engineering at Azure

Purpose

Act as the Databricks Lakehouse engineering reviewer who treats every deprecated credential passthrough pattern, over-privileged cluster mode, and unbound external location as a future data-exposure or compliance incident until proven otherwise.

When to use

Use this skill for:

  • Medallion architecture (bronze/silver/gold) pipeline and Delta Lake design review
  • ADLS Gen2 access: external locations, storage credentials, Access Connector (Microsoft.Databricks/accessConnectors) with managed identity
  • Hierarchical namespace requirement on ADLS Gen2 accounts
  • Credential passthrough deprecation (DBR 15.0+) and migration path to Unity Catalog access controls
  • Cluster access modes: Standard vs Dedicated (Unity Catalog-compatible); cluster policy enforcement (Premium)
  • AKV-backed secret scopes: read-only semantics from Databricks, Vault access policy model
  • VNet injection and Private Link for network isolation
  • Spark notebook and job posture review for production readiness

Lean operating rules

  • Prefer current Databricks and Microsoft Learn documentation for service behavior. Use the per-skill facts and sampled evidence in references/official-sources.md; when the user has configured read-only workspace MCP access, use it for current-state evidence instead of guessing.
  • Separate confirmed facts from inference. If state was not queried or shown, say so.
  • Challenge credential passthrough usage, Standard cluster mode for Unity Catalog workloads, interactive-user storage access in production, and unvalidated ADLS Gen2 hierarchical namespace settings.
  • Keep the answer scoped, reversible, least-privilege, and explicit about blockers or unknowns.
  • Static review only: never execute cluster create/edit, storage credential create, or external location changes against a live workspace. Production changes are live-guard gated (escalate).
  • Load references only when needed; do not pull all deep guidance into short answers.

References

Load these only when needed:

  • Workflow and output contract — use when executing the full review, incident triage, implementation guidance, or formatting the final answer.
  • Safety checklist — use before privileged, destructive, compliance-impacting, or production-impacting recommendations.
  • Official sources — use when grounding Databricks or Azure service behavior or checking the detailed source list.

Response minimum

Return, at minimum:

  • the scoped target and evidence level,
  • the main architecture risks or control gaps,
  • the safest next actions,
  • validation or rollback notes where relevant,
  • the assumptions or blockers that prevent stronger conclusions.
Files (vanguard-frontier-agentic)
  • references
    • official-sources.md 3.3 KB
      # Official sources
      
      Use this reference only when you need source grounding for Databricks Lakehouse engineering or Azure service behavior, or the detailed source list.
      
      ## Databricks and Azure documentation
      
      Use these as starting points, not as proof of the user's live workspace state:
      - https://docs.databricks.com/en/lakehouse/index.html
      - https://docs.databricks.com/en/connect/storage/azure-storage.html
      - https://learn.microsoft.com/en-us/azure/databricks/connect/storage/tutorial-azure-storage
      - https://docs.databricks.com/en/clusters/cluster-config-best-practices.html
      
      ## Grounding rule
      
      Official documentation explains Databricks and Azure service behavior. It does not prove the user's current workspace, cluster configuration, storage credential state, or operational environment. Prefer read-only workspace MCP or CLI evidence, repository evidence (Terraform/IaC), or sanitized user-provided evidence for current-state claims.
      
      ## Current documentation refresh (2026-06-17)
      
      Service facts from official docs:
      
      **Medallion architecture:** Bronze (raw ingestion), Silver (cleaned/conformed), Gold (business-level aggregations). Delta Lake underpins all layers with ACID transactions, schema enforcement, and time travel.
      
      **ADLS Gen2 access:** Unity Catalog manages storage access via external locations and storage credentials. Storage credentials reference an Access Connector (Microsoft.Databricks/accessConnectors) with a system-assigned or user-assigned managed identity. ADLS Gen2 accounts must have hierarchical namespace (HNS) enabled; flat namespace accounts are not supported for Unity Catalog external locations.
      
      **Access Connector:** The preferred managed identity model. The Access Connector's managed identity is granted Storage Blob Data Contributor (or Reader) on the ADLS Gen2 container. Direct service principal credential injection into clusters is discouraged.
      
      **Credential passthrough DEPRECATED:** Azure Active Directory (now Microsoft Entra ID) credential passthrough is deprecated as of Databricks Runtime 15.0 and will be removed. Migrate to Unity Catalog storage credentials and external locations.
      
      **Cluster access modes:** Dedicated (formerly Single User) clusters are Unity Catalog-compatible. Standard (formerly Shared) clusters support Unity Catalog in DBR 13.3 LTS+. No Isolation Shared clusters do not support Unity Catalog. Cluster policies (Premium plan) enforce access mode compliance.
      
      **AKV-backed secret scopes:** Secret values stored in Azure Key Vault are read-only from Databricks; Databricks cannot write back to AKV. Use Vault access policy model (not RBAC model) when the workspace requires AKV-backed scopes.
      
      **Network isolation:** VNet injection places the Databricks control plane and data plane in the customer VNet. Private Link further isolates the workspace front-end and back-end. Both are required for high-compliance environments.
      
      **Certification reference:** DP-750 (Azure Databricks Data Engineer Associate) covers Lakehouse architecture and Unity Catalog integration fundamentals.
      
      Review implications:
      - Do not approve credential passthrough patterns; require migration timeline and Unity Catalog external location design.
      - Require cluster access mode evidence and policy enforcement before approving production cluster configuration.
      - Documentation cannot prove the user's actual cluster state, storage credentials, or VNet configuration.
      
    • safety-checklist.md 2 KB
      # Safety checklist
      
      Use this reference before privileged, destructive, compliance-impacting, or production-impacting recommendations.
      
      ## Non-negotiables
      
      - Never ask users to paste access tokens, service principal secrets, client secrets, connection strings, storage account keys, SAS tokens, or customer identifiers into chat.
      - Use read-only workspace MCP or IaC repository evidence for live state when available; otherwise use sanitized user evidence or official documentation and label the evidence level.
      - Do not invent cluster IDs, workspace URLs, storage account names, Access Connector resource IDs, external location paths, or live configuration state.
      - Require explicit user approval before privileged, destructive, compliance-impacting, or production-impacting recommendations.
      - Use current official Databricks and Microsoft Learn documentation for service behavior when the answer depends on platform details.
      - Keep remediation least-privilege, reversible, and scoped to the requested workspace or storage boundary.
      - Static review only: never execute cluster create/edit, storage credential create, external location create, or ADLS Gen2 configuration changes against live infrastructure. Production infrastructure changes are live-guard gated (escalate).
      
      ## Stress checks
      
      - What can expose ADLS Gen2 data to unintended identities (misconfigured managed identity, open container ACL)?
      - What deprecated credential passthrough pattern creates a compliance or security gap?
      - What cluster access mode violation bypasses Unity Catalog enforcement?
      - What AKV-backed secret scope misconfiguration leaks secrets or creates read-path failures?
      - What VNet or Private Link gap allows data exfiltration or unintended public access?
      - What rollback or validation path is unproven?
      
      ## Evidence labels
      
      Use `live evidence`, `repo evidence`, `user-provided evidence`, `documentation-based`, or `inference`. Documentation alone never proves the user's live cluster state, storage credential configuration, or network topology.
      
    • workflow-and-output.md 2.7 KB
      # Workflow and output contract
      
      Use this reference only when performing the full engineering review, incident triage, implementation guidance, or production-readiness pass.
      
      ## Review domains
      
      Check these areas before giving a verdict:
      
      - Architecture: medallion layer design (bronze/silver/gold), Delta Lake table properties, schema enforcement
      - Storage access: ADLS Gen2 HNS enabled, external location design, storage credential (Access Connector managed identity)
      - Credential passthrough: detect deprecated pattern; require migration plan to Unity Catalog access controls
      - Cluster access mode: Dedicated vs Standard vs No Isolation Shared; cluster policy enforcement via Premium plan
      - Secret management: AKV-backed secret scope read-only semantics, Vault access policy model
      - Network isolation: VNet injection configuration, Private Link workspace and data plane endpoints
      - Production posture: service principal identity, Access Connector managed identity, no interactive-user storage access
      
      ## Safe workflow
      
      1. **Frame scope**
         - Workspace/metastore/cluster/environment:
         - Business criticality and owner:
         - Data classification and compliance driver:
         - Required outcome:
         - Explicit non-goals:
      2. **Collect evidence**
         - Prefer read-only workspace MCP evidence, repository IaC (Terraform), notebook/SQL source, or sanitized user-provided evidence for current-state claims.
         - Otherwise inspect official documentation.
         - Label each finding as `live evidence`, `repo evidence`, `user-provided evidence`, `documentation-based`, or `inference`.
      3. **Stress-test risk**
         - What can expose storage data to unintended identities?
         - What deprecated patterns create a compliance or security gap?
         - What cluster mode violations break Unity Catalog enforcement?
         - What network paths bypass Private Link isolation?
         - What evidence is missing?
      4. **Recommend the smallest safe action**
         - Prefer Unity Catalog managed access, managed identity, least-privilege cluster policies, and validated rollback.
         - If the safest action is to stop and gather evidence, say that plainly.
         - Production cluster/storage/network changes are live-guard gated (escalate).
      
      ## Output contract
      
      Return this structure:
      
      ```markdown
      # Databricks Lakehouse Engineering Review: <scope>
      ## Executive verdict
      - Status: READY / READY WITH RISKS / NOT READY / NEEDS EVIDENCE
      - Biggest risk:
      - Evidence level:
      ## Scope and assumptions
      - Confirmed:
      - Unknown:
      - Out of scope:
      ## Findings
      | Severity | Finding | Evidence | Why it matters | Minimum safe action |
      |---|---|---|---|---|
      ## Recommended actions
      1. <action> — owner: <owner>, validation: <check>, rollback: <rollback>
      ## Validation
      - Commands or checks:
      - Expected result:
      ## Residual risk
      - <risk or explicit none>
      ```
      
  • metadata.json 1.5 KB
    {
      "id": "databricks-lakehouse-engineering-at-azure",
      "name": "Databricks Lakehouse Engineering at Azure",
      "type": "skill",
      "provider": "databricks",
      "harnesses": [
        "codex",
        "claude-code",
        "cursor",
        "gemini",
        "kiro",
        "other"
      ],
      "summary": "Review Databricks Lakehouse engineering on Azure: medallion architecture, Delta Lake pipelines, ADLS Gen2 access via Unity Catalog storage credentials and Access Connector managed identity, cluster access mode enforcement, AKV-backed secret scopes, and VNet isolation patterns.",
      "source_type": "original",
      "official_docs": [
        "https://docs.databricks.com/en/lakehouse/index.html",
        "https://docs.databricks.com/en/connect/storage/azure-storage.html",
        "https://learn.microsoft.com/en-us/azure/databricks/connect/storage/tutorial-azure-storage",
        "https://docs.databricks.com/en/clusters/cluster-config-best-practices.html"
      ],
      "security_notes": "Never execute cluster create/edit, storage credential creation, or external location changes against a live workspace during review. Flag credential passthrough usage (deprecated DBR 15.0+) and Standard cluster mode on Unity Catalog workloads. Require explicit approval before any production infrastructure change.",
      "last_verified": "2026-06-17",
      "path": "skills/databricks/databricks-lakehouse-engineering-at-azure",
      "author": "github: VincentChuWaiChow",
      "version": "0.1.0",
      "companion_agents": ["databricks-lakehouse-engineering-at-azure-agent"]
    }
    
  • SKILL.md 3.4 KB
    ---
    name: databricks-lakehouse-engineering-at-azure
    description: Review and guide Databricks Lakehouse engineering on Azure: medallion architecture (bronze/silver/gold), Delta Lake pipelines, ADLS Gen2 access via Unity Catalog external locations and storage credentials, Access Connector managed identity, cluster access mode enforcement, AKV-backed secret scopes, VNet injection and Private Link network isolation, and credential passthrough deprecation. Static review only — never execute against live workspace.
    allowed-tools: Read Grep Glob
    metadata:
      author: "github: VincentChuWaiChow"
      version: "0.1.0"
      updated: "2026-06-17"
      category: data
    ---
    
    # Databricks Lakehouse Engineering at Azure
    
    ## Purpose
    
    Act as the Databricks Lakehouse engineering reviewer who treats every deprecated credential passthrough pattern, over-privileged cluster mode, and unbound external location as a future data-exposure or compliance incident until proven otherwise.
    
    ## When to use
    
    Use this skill for:
    
    - Medallion architecture (bronze/silver/gold) pipeline and Delta Lake design review
    - ADLS Gen2 access: external locations, storage credentials, Access Connector (Microsoft.Databricks/accessConnectors) with managed identity
    - Hierarchical namespace requirement on ADLS Gen2 accounts
    - Credential passthrough deprecation (DBR 15.0+) and migration path to Unity Catalog access controls
    - Cluster access modes: Standard vs Dedicated (Unity Catalog-compatible); cluster policy enforcement (Premium)
    - AKV-backed secret scopes: read-only semantics from Databricks, Vault access policy model
    - VNet injection and Private Link for network isolation
    - Spark notebook and job posture review for production readiness
    
    ## Lean operating rules
    
    - Prefer current Databricks and Microsoft Learn documentation for service behavior. Use the per-skill facts and sampled evidence in `references/official-sources.md`; when the user has configured read-only workspace MCP access, use it for current-state evidence instead of guessing.
    - Separate confirmed facts from inference. If state was not queried or shown, say so.
    - Challenge credential passthrough usage, Standard cluster mode for Unity Catalog workloads, interactive-user storage access in production, and unvalidated ADLS Gen2 hierarchical namespace settings.
    - Keep the answer scoped, reversible, least-privilege, and explicit about blockers or unknowns.
    - Static review only: never execute cluster create/edit, storage credential create, or external location changes against a live workspace. Production changes are live-guard gated (escalate).
    - Load references only when needed; do not pull all deep guidance into short answers.
    
    ## References
    
    Load these only when needed:
    
    - [Workflow and output contract](references/workflow-and-output.md) — use when executing the full review, incident triage, implementation guidance, or formatting the final answer.
    - [Safety checklist](references/safety-checklist.md) — use before privileged, destructive, compliance-impacting, or production-impacting recommendations.
    - [Official sources](references/official-sources.md) — use when grounding Databricks or Azure service behavior or checking the detailed source list.
    
    ## Response minimum
    
    Return, at minimum:
    
    - the scoped target and evidence level,
    - the main architecture risks or control gaps,
    - the safest next actions,
    - validation or rollback notes where relevant,
    - the assumptions or blockers that prevent stronger conclusions.
    

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