Architecture Patterns & Transformation Scenarios

A regional bank managing 15+ years of core-banking data across fragmented on-premise Oracle instances — manual ETL scripts, no data lineage, no schema enforcement.

Deployed Medallion-as-Code: Terraform-provisioned Azure Databricks workspace, Databricks Asset Bundles for CI/CD, dbt transformations with strict schema contracts at each Medallion layer. Unity Catalog lineage and ACLs embedded from Bronze ingestion onward.

Zero-data-loss migration. Schema contracts enforced at every layer boundary. Bronze → Silver → Gold on Azure Databricks.

A telecom operator with existing Databricks pipelines but no visibility into schema drift, cost anomalies, or compliance gaps. Pipeline failures discovered reactively — by the CFO asking why the cloud bill doubled.

Deployed AI-driven audit: analyzed Delta Lake table schemas, Unity Catalog ACL configurations, job cluster utilization patterns, and pipeline failure logs. Delivered a scored report with 4 severity tiers and a 12-week remediation roadmap ranked by ROI.

23 architectural anti-patterns identified. 6 governance gaps flagged. Prioritized remediation roadmap delivered in 8 days.

An insurance group operating in both Senegal and Québec with HR, claims, and policyholder data spanning two regulatory regimes. Manual compliance checks taking 3+ weeks per audit cycle. Risk of cross-border data residency violations.

Implemented Unity Catalog governance mesh: automated PII classifiers with agent-driven detection, retention policy agents enforcing CDP and Law 25 timelines, cross-workspace Delta Sharing with residency controls, and auto-generated audit packs delivered to compliance officers on schedule.

CDP + Law 25 compliance achieved simultaneously. Agent-driven PII detection covering 4.7M records. Automated audit packs generated weekly.

A fintech processing 2.3M mobile-money transactions daily across 8 West African markets. Pipeline failures — schema mismatches, late-arriving data, partition skew — caused downstream reporting delays and SLA breaches. The on-call data team was burning out.

Deployed a multi-agent triage mesh (Google ADK + custom routing agents): a monitoring agent detecting anomalies in Delta Live Table metrics, a diagnostic agent correlating failure patterns against a knowledge base of known issues, and a remediation agent with graduated autonomy — auto-fix for known patterns, human-in-the-loop escalation for novel failures. Full audit trail on every agent decision.

Mean Time To Resolution (MTTR) reduced from 4.2 hours to 12 minutes. 73% of pipeline anomalies auto-remediated without human intervention.

A national retailer with a 12-person internal data team stuck on legacy SQL Server + SSIS — unable to adopt Databricks despite having procured the licenses. The team had the domain knowledge but zero Medallion architecture experience.

Embedded pair-architecting sprints: our principal architect co-designed the first Bronze → Silver → Gold pipeline with their senior data engineer, then supervised two subsequent pipelines built by their team independently. Delivered runbooks, CI/CD templates, and Unity Catalog configuration guides. After 8 weeks, their team owned the platform — we transitioned to quarterly architecture review calls only.

6 internal data engineers certified on Medallion architectures. 3 pipelines production-ready after 8-week pair-architecting sprint. Team operating independently within 12 weeks.