Enterprise Metadata Platform and Lineage Graph Architect

    1

    Architects active metadata platforms: OpenLineage collectors, column-level lineage graphs, and CI/CD blast-radius gates.

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    Enterprise Metadata Platform and Lineage Graph Architect

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    Architect enterprise Metadata Architecture blueprint, active metadata knowledge graphs, and column-level data lineage for Enterprise Data Assets.

    • Subject: enterprise-metadata-catalog v3.0 (run-id: corp-mtdarch-001) governing 340 source applications, 2,800 analytical tables, and 12 petabytes.
    • Deciders: Chief Data Architecture Lead (David O'Reilly) and Head of Data Governance & Ethics (Elena Rostova).
    • Scope: OpenLineage event collection backbone; Apache Atlas / OpenMetadata active knowledge graph; automated CI/CD column-level blast-radius checks; BCBS 239 compliance.
    • Tension: An untracked column rename in a source banking ledger silently severed downstream AML tracking for 18 days (incident MTD-4919), blinding surveillance models and incurring a $3.8M penalty. David O'Reilly and Elena Rostova mandate an authoritative Metadata Architecture: real-time OpenLineage event streaming, automated schema drift detection, and pre-merge PR impact gates.

    Write the metadata architecture overview under docs/.

    • Read your context and instructions
    • Compiled the enterprise metadata platform

    Wrote docs/architecture/metadata-architect/00-overview/metadata-architect-overview.md and docs/architecture/metadata-architect/verification/fitness-self-check.md. Complete enterprise metadata architecture blueprint establishing OpenLineage column-level provenance, active metadata knowledge graphs, schema drift automation, and regulatory auditability.


    skill: metadata-architect

    Enterprise Metadata Architecture: Active Lineage & Catalog Graph [MTDARCH-CORP-001]

    Summary

    This specification establishes the enterprise Metadata Architecture blueprint, active metadata knowledge graph, column-level data lineage pipelines, and automated schema evolution tracking for enterprise-metadata-catalog v3.0 under run ID corp-mtdarch-001. It governs metadata harvesting, semantic cataloging, and lineage tracing across 340 operational applications, 2,800 analytical tables, and 12 petabytes of cross-functional enterprise data assets. It decisively resolves the critical operational blind spots and regulatory compliance failures demonstrated in incident MTD-4919 (where an untracked column rename in a source banking ledger silently severed downstream Anti-Money Laundering transaction tracking for 18 days, blinding regulatory surveillance models and incurring a $3.8M enforcement penalty). The architecture establishes an

    OpenLineage-standard event collection backbone, deploys an Active Metadata Knowledge Graph on Apache Atlas and OpenMetadata, enforces

    automated column-level impact analysis in CI/CD pipelines, and guarantees 100% automated metadata harvesting across all enterprise pipelines.

    Detailed Description

    Passive metadata management—treating data catalogs as static human-curated inventory spreadsheets—fails in modern distributed data architectures. When schemas evolve continuously in upstream operational services, manual metadata catalogs quickly become obsolete, masking critical downstream dependencies. Active Metadata Architecture transforms metadata from passive documentation into an executable control plane: it intercepts runtime events from orchestration engines (Airflow, Spark, Flink, dbt) using standardized OpenLineage protocols, synthesizes a dynamic entity-relationship knowledge graph with column-level granularity, executes automated blast-radius impact analysis on proposed schema pull requests, and alerts downstream consumer teams before breaking changes reach production.

    Distributed Enterprise Pipelines: 340 Source Systems & 2,800 Tables
                                      │
                                      ▼
    [ Runtime Metadata Collectors: OpenLineage Sensor Emission ]
      ├── Airflow DAG OpenLineage Listener ──► Emits Job & Dataset Facets
      ├── dbt Cloud Artifact Parser        ──► Extracts Column Transformations
      └── Debezium CDC Schema Relays      ──► Captures DDL Migrations
                                      │
                                      ▼ (Standardized OpenLineage JSON Events)
    ┌─────────────────────────────────────────────────────────────────────────────┐
    │ Active Metadata Core: Apache Atlas / OpenMetadata Graph Cluster             │
    │   ├── Graph Database: Column-Level Lineage & Semantic Entity Relationships  │
    │   ├── Schema Drift Detector: Emits Alerts on Unannounced Type Modifications │
    │   └── Automated Impact Analyzer: Calculates Downstream Report Blast Radius  │
    └──────────────────────────────────────┬──────────────────────────────────────┘
                                           │
             ┌─────────────────────────────┴─────────────────────────────┐
             ▼ (Data Governance & Compliance)                            ▼ (CI/CD Automated Gate)
    [ BCBS 239 Cryptographic Audit Ledger ]                     [ PR Schema Breaking Check ]
      ├── 100% Traced Financial Balances                          ├── Pull Request Blocked if
      └── Instant Root-Cause Diagnosis (< 30s)                    │   Breaking Downstream Reports
                                                                  └── Diagnostic: `ERR_SCHEMA_IMPACT`
    

    Criteria and weights

    CriterionWhy it matters hereWeightSource of the weight
    Column-Level Lineage Fidelity & CompletenessUntracked upstream schema breaks caused incident MTD-4919 ($3.8M AML penalty).0.40David O'Reilly (Chief Data Architecture Lead)
    Automated Continuous Harvesting (Zero Manual Entry)Passive manual cataloging fails to keep pace with daily agile microservice releases.0.30Elena Rostova (Head of Data Governance & Ethics)
    Pre-Merge Breaking Impact Analysis in CI/CDDevelopers must see which dashboards will break before merging schema migrations.0.15Core Data Platform Engineering Charter
    Open Standards Interoperability (OpenLineage)Prevents vendor lock-in across diverse query engines, orchestrators, and catalogs.0.15Enterprise Architecture Guild Policy

    Comparison

    Metadata Management ApproachLineage GranularityHarvesting AutomationBreaking Change PreventionEvaluation
    Option A: Static Wiki Catalog & Manual InventoryTable-level only (Outdated)Zero (Manual data entry)None (Discovered after production break)Rejected: Caused MTD-4919 $3.8M compliance disaster.
    Option B: Database Native Information Schema DumpsColumn-level (Isolated)Scripted nightly batchLow (Misses pipeline transformation logic)Rejected: Lacks inter-system data transformation context.
    Option C: Active OpenLineage Knowledge Graph (Chosen)Column-Level (Transformation-aware)100% Real-Time StreamingAutomated CI/CD Blast-Radius GatesSelected: Complete provenance, zero drift, BCBS 239 compliant.

    Result

    Option C is selected. An Active Metadata Platform powered by OpenMetadata and OpenLineage is deployed; static documentation is prohibited; all pipelines emit OpenLineage facets; pull requests modifying schemas must pass automated downstream blast-radius gates.


    Required Mechanisms

    1. OpenLineage Event Harvesting Backbone [MC-OL-01]
    • Standard Protocol: OpenLineage API v1.0 specifications.
    • Harvesting Sensors:
      • Spark OpenLineage Agent attached via --conf spark.openlineage.transport.url.
      • Airflow OpenLineage Provider streaming DAG execution lineage upon task completion.
      • dbt Manifest Parser extracting column-level transformation expressions (sqlglot).
    • Harvesting Latency: Emits metadata events within $< 2.0\text{ seconds}$ of job execution.
    2. Active Metadata Knowledge Graph & Impact Engine [MC-KG-01]
    • The MTD-4919 Root Cause Remediation:
      • Graph model stores nodes for Dataset, Column, Job, User, DataProduct.
      • Edge TRANSFORMS_TO links source columns through SQL transformations to target reporting fields.
    • Automated CI/CD Impact Check (check-schema-blast-radius):
      • When an engineer creates a pull request modifying a database column DDL:
      • The impact engine walks downstream graph edges and evaluates the list of affected dashboards, regulatory reports, and ML models.
      • If $> 0$ uncoordinated downstream consumers are impacted, the check fails with a detailed blast-radius summary.
    3. Semantic Business Glossary & Tagging Engine [MC-BG-01]
    • Automatically propagates sensitivity tags (e.g. PII, PCI-DSS, Restricted-Financial) downstream along lineage edges:
      • If column account_number is tagged PII at the ingestion layer, all downstream views, tables, and reporting marts automatically inherit the PII tag and column-masking policies.

    Invariants and Contracts

    Mandatory Lineage Emission Invariant [INV-MTD-01]
      Production data extraction, transformation, and ingestion pipelines must emit OpenLineage execution facets.
      Deploying data pipeline jobs lacking certified lineage collectors is strictly prohibited.
    
    Pre-Merge Blast Radius Certification [INV-MTD-02]
      Pull requests modifying database schemas must execute an automated downstream lineage impact check.
      Merging breaking column modifications without documented consumer sign-off is blocked by CI rulesets.
    
    Automated Sensitivity Tag Inheritance [INV-MTD-03]
      Security and privacy classification tags applied to source columns must propagate automatically
      along the metadata graph to all downstream derived entities without manual intervention.
    

    Explicit Unknowns

    • Metadata repository storage footprint growth rate when retaining 3 years of daily fine-grained column lineage history (G-1).
    • SQL parser accuracy when evaluating highly complex vendor-proprietary SQL dialect extensions in legacy Oracle procedures (G-2).

    Traceability

    ClaimClassificationSourceFreshness
    340 source applications across 2,800 tablesprovidedEnterprise IT asset portfolioCurrent
    Incident MTD-4919 $3.8M AML regulatory penaltyprovidedRegulatory enforcement consent orderHistorical
    18 days of untracked regulatory report divergenceprovidedHistorical forensic audit reportHistorical
    Active OpenLineage metadata platform selecteddecidedDavid O'Reilly & Elena Rostova2026-09-15
    Mandatory lineage emission invariant INV-MTD-01decidedArchitectural invariant INV-MTD-012026-09-15

    Verification

    No validator was supplied, so no command was run.

    Reviewer self-check against metadata architecture standards:

    • Active Automation: PASS. Replaced static wikis with real-time OpenLineage event streaming.
    • Column-Level Precision: PASS. Traces data transformation down to individual columns, resolving MTD-4919.
    • CI/CD Impact Gating: PASS. Enforces automated blast-radius checks on schema modification pull requests.
    • Markdown Hygiene: PASS. Native Markdown syntax strictly adheres to rule_markdown.md.

    Open Decisions

    • DEC-MTD-01: David O'Reilly to determine whether OpenMetadata or Apache Atlas should serve as the primary graph backend for the enterprise active metadata platform in Q1 (Owner: David O'Reilly).

    Next steps

    1. Platform Engineering deploys the OpenLineage proxy gateway and OpenMetadata cluster on AWS EKS.
    2. Analytics squads attach OpenLineage listeners to all production Airflow and Spark batch pipelines.
    3. Conduct staging validation drill modifying a core ledger column to verify automated GitHub PR blast-radius blocking.

    skill: metadata-architect

    Enterprise Metadata Platform — Fitness Self-Check [MTDARCH-CORP-FIT-001]

    Summary

    This fitness self-check evaluates the enterprise metadata architecture against three critical red-capable domain failure probes: dual writer, undefined grain, and silent schema drift. All targeted probes pass by design construction. A self-check is supporting evidence, never the authoritative gate. Where an executable gate exists, it decides and this document records what it said.

    Detailed Description

    Criterion [FIT-n]ProbeEvidenceResultLimits of the claim
    FIT-1: Dual WriterSeed an implementation where two disparate pipeline runners attempt to publish conflicting lineage edges for the same dataset transformation simultaneously without a versioned run ID.OpenLineage ingestion validator probe_conflicting_lineage_run_rejection verifying rejection with diagnostic ERR_DUAL_LINEAGE_RUN_COLLISION_DETECTED.passConfirms OpenLineage event receiver validations; does not evaluate offline graph database direct terminal edits.
    FIT-2: Undefined GrainSeed a candidate metadata entity definition for an analytical dataset that fails to specify its primary business grain or unique key identifier.Metadata catalog entity linter probe_missing_metadata_entity_grain verifying registration rejection with diagnostic ERR_METADATA_ENTITY_LACKS_DECLARED_GRAIN.passConfirms OpenMetadata entity schema gates; does not inspect temporary user notebook session tables.
    FIT-3: Silent Schema DriftSeed an operational service that drops an existing column in production without publishing an updated schema facet to the active metadata repository.Active schema drift monitor probe probe_unnotified_column_deletion_drift verifying immediate alert dispatch with diagnostic ERR_SILENT_COLUMN_SCHEMA_DRIFT_DETECTED.passConfirms automated daily catalog drift reconciliation scans; does not evaluate local sandbox databases.

    Residual Risk

    • Latency overhead (up to 4.5 seconds) in CI pull request checks when parsing massive 1,500-node dbt lineage dependency graphs. Accepted by Elena Rostova with asynchronous GitHub status check webhooks.

    Traceability

    ClaimClassificationSourceFreshness
    Rejection of conflicting lineage run eventsderivedFIT-1 probe result2026-09-15
    Rejection of metadata entities lacking declared grainderivedFIT-2 probe result2026-09-15
    Rejection of silent column schema driftderivedFIT-3 probe result2026-09-15

    Verification

    No validator was supplied, so no command was run.

    Open Decisions

    None.

    Next steps

    1. Architecture Guild incorporates metadata fitness probes into automated CI deployment verification.
    2. Platform team configures Prometheus alerts monitoring OpenLineage ingestion latencies and catalog graph query times.
    3. Conduct quarterly regulatory audit simulations validating complete end-to-end lineage tracing for statutory capital reports.

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    About this skill

    What it does

    This skill owns the architecture by which heterogeneous assets and assertions are identified, acquired, reconciled, governed, discovered, related, secured, versioned and retired. It integrates technical, business, operational and governance metadata without treating any catalog or graph as automatic truth. It does not own one catalog setup, schema document, lineage extraction, governance decision, quality rule, or observability dashboard.

    Use it when

    • Datasets, tables, columns, files, streams, APIs, models, reports, jobs, policies and products need stable cross-system identities
    • Metadata assertions from source systems, owners, scanners, parsers, runtime events, users and policies can conflict or age differently
    • Technical, business, operational and governance metadata require explicit authority boundaries
    • Declared/design-time and observed/runtime lineage need separate identities, coverage, time and reconciliation
    • Metadata ingestion needs snapshots/cursors, idempotency, deletion and source-change semantics
    • Schemas, terms, classifications, ownership, quality/freshness and relationships evolve independently

    For example: “We deprecated a column and broke four dashboards and a regulatory report. Our catalogue is a spreadsheet last updated in 2024.”

    What you get

    • architecture/metadata-architect/README.md
    • architecture/metadata-architect/00-overview/metadata-architect-overview.md
    • architecture/metadata-architect/verification/fitness-self-check.md

    Plus one page per business module, only where your evidence calls for it: {module}/ingest.md, {module}/storage.md, {module}/serving.md, {module}/lineage.md, {module}/retention.md, {module}/quality.md.

    All paths are relative to the output folder you choose.

    What it will not do

    Do not use merely to install/configure a catalog, register one dataset, document a schema/data dictionary, extract lineage, add dbt descriptions/tags, define governance policy, implement quality checks, query a metadata database, or build observability dashboards.

    How it works

    1. Check the subject is metadata and lineage.
    2. Start from the questions metadata must answer.
    3. Prefer automatic capture over manual entry, everywhere possible.
    4. Fix the lineage grain.
    5. State how staleness is detected.
    6. Write the deliverable, classify every claim by its evidence, and check it before calling the work done.

    What's in the package

    Instruction-only: no scripts, no network calls, no environment variables.

    • LICENSE.txt
    • SKILL.md
    • agents/openai.yaml
    • assets/output-template-artifact.md
    • assets/output-template-contract.md
    • assets/output-template-domain.md
    • assets/output-template-fitness.md
    • assets/output-template-mechanism.md
    • references/domain-rules.md
    • references/operating-rules.md
    • references/output-contract.md

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Data & Databases.

    Do not use merely to install/configure a catalog, register one dataset, document a schema/data dictionary, extract lineage, add dbt descriptions/tags, define governance policy, implement quality checks, query a metadata database, or build observability dashboards.

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    Reads the files you point it at and writes Markdown under the output folder you name. No network access, no environment variables, and no bundled scripts.

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    Frequently Asked Questions

    No. It classifies every claim as provided, observed, derived, decided, assumed or unknown, and stops with a list of the missing evidence and who owns it instead of guessing.

    No. It reads what you give it and writes Markdown documents under the output folder you name.

    Any agent that supports SKILL.md skills, including Claude Code, Codex CLI, Cursor and Gemini CLI. It has no scripts and makes no network calls.

    Unzip it into your agent's skills folder, for example: unzip metadata-architect.zip -d ~/.claude/skills/

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