Audited Production Track Record · 7 Enterprise Case Studies · 20+ Years Principal Pedigree

Verified Engineering Outcomes Under Extreme Enterprise Load.

Every architectural blueprint in the Archeon Cloud Engine (ACE) was forged solving mission-critical problems for global telecoms, national rail operators, Tier-1 investment banks, private equity carve-outs, and sovereign governments.

01Türk Telekom (300k rec/sec) 02Siemens Mobility (£1.6B Rail) 03Yahoo Inc. ($5B M&A) 04LC Waikiki (100% Crash-Free) 05Lockheed Martin (80 TB Police) 06BAML & Banking (>£1M/yr FinOps) 07Sovereign Tax (19x Scale)

Case Study 01 · Tier-1 Telecom · Streaming, Exadata RAC & Agentic Data Factory Türk Telekom & AVEA · 50M+ Subscribers · Oracle Innovation Award

300k/s Zero-Copy Streaming, 10-Node Oracle Exadata RAC Deep Tuning & AI-Assisted / Agentic Data Development Factory

Operating across Landline, Broadband, and Mobile (GSM) domains serving 50M+ subscribers on an asymmetric 10-node Oracle Exadata RAC cluster (8x X9M-2 + 2x X10M mega-nodes, 17 storage cells, 896 physical cores / 1,792 hardware threads, ~11 TB RAM, 94.48% Smart Scan filtering across 403.8 PB, 25B-26B rows/day across 2,120+ concurrent sessions), the enterprise faced 14.5-hour EL load phases, nightly batch SLA overruns, 512 caged hardware threads on X10M expansion nodes, 11,635 minutes of sort extent pool latch serialization, ~18.6 TB daily broadcast temp spills, 169.3 hours of enq: HV lockouts, and 36.5 billion daily blind updates.

Principal Architecture & Engineering Delivered

PyArrow C++ Zero-Copy Streaming Ingestion: Engineered a real-time CDR ingestion engine using PyArrow C++ native zero-copy decompression, Celery 5.6+, Redis 8.x, Linux inotify, and a live FastAPI SSE dashboard, processing 200,000 compressed archives daily (~20 TB compressed, >20.5B records) at up to ~300,000 records/sec under an 80 MB RAM ceiling (cutting EL windows from 14.5h to 3.5h at 1/10th CPU/RAM cost).
10-Node Exadata RAC Uncaging & DBRM v5.0 Architecture: Uncaged +512 trapped hardware threads (+40% cluster CPU capacity) on X10M nodes, calibrated proportional PGA memory (350 GB / 650 GB preventing >4 PB disk spills) and parallel_force_local = TRUE BI logon triggers, and deployed the 2-window DBRM v5.0 resource plan (DWH_ETL_NIGHT_PLAN & DWH_DSS_DAY_PLAN anchored to UTC+3) - collapsing resmgr:cpu quantum waits by 99.9% (down to 1.12m), stopping 14,567-slave parallel query leaks, slashing nightly batch turnaround by 5.0 hours/day, and recovering 975.9 CPU hours/month (-22.3% compute savings).
Non-Invasive CBO SQL Patching, Storage & HyperLogLog Stats: Deployed non-invasive DBMS_SQLDIAG SQL Patches & Profiles eliminating ~18.6 TB/day of PX SEND BROADCAST temp spills without touching legacy ETL code; refactored 2.85B-row outer DISTINCT queries from 130.5 hours DB time (798 GB temp spill) to <2 minutes; eliminated 36.5B daily blind updates; eradicated 100% of enq: SS contention (105.9h to 0.00m) and 98.4% of sort latch waits via 32 MB / 64 MB uniform temp extents; rebuilt 14 high-concurrency staging tables with 16-bucket Hash Partitioning to eradicate 99.6% of enq: HV lockouts (169.3h to 0h) and reclaim 89.3% NVMe storage; engineered a HyperLogLog incremental bulk statistics engine across 68,000+ partitions; and tuned Linux HugePages (132 GB), TCP buffers (134 MB), and JDBC fetch/batch arrays (140x fewer roundtrips), accelerating core ETL pipelines by 89.6% to 98.0%.
AI-Assisted / Agentic Data Development Factory: We developed specialized AI Skills and MCP solutions for Data Engineering, Data Vault 2.1 / TM Forum SID Architecture, Governance development/audit (Apache Ranger & Atlas), and DB Performance Tuning, paired with a programmatic dbt-to-ODI 12c SDK bridge and our "Loop Engineering" Agentic Developer OS.

~300,000/s Zero-copy streaming under <80 MB RAM (EL cut 14.5h → 3.5h at 1/10th cost)

+40% CPU · -5h +512 Exadata threads uncaged · nightly batch cut by 5.0h/day (-22.3% CPU)

99.9% & 100% 99.9% CPU quantum wait collapse · 100% enq: SS & 99.6% enq: HV eradicated

130.5h → <2m Query refactored · 18.6 TB/day broadcast spills eliminated · 89.6-98% faster ETL

89.3% NVMe Staging NVMe reclaimed + 3,047.8 CPU mins saved via HCC/DOP surgery

10x & ~60% 10x developer velocity & ~60% faster onboarding via Agentic Data Factory

Oracle Exadata 10-Node RAC DBRM v5.0 & SQL Patches 16-Way Hash & 32M/64M Temp HyperLogLog Incremental Stats PyArrow C++ Zero-Copy Data Vault 2.1 & dbt Semantic Layer Agentic Data Development Factory AI Skills & FastMCP

Case Study 02 · Industrial IoT, Rail & Predictive Maintenance Siemens Mobility · £1.6B UK Rail Contract

Scaling UK National Rail IIoT Telemetry by 400% (50M+ Daily Sensor Files) Across 60+ AWS Microservices

Under a £1.6B UK rolling-stock maintenance and digital-twin program, high-frequency onboard train sensors transmitted tens of millions of complex nested JSONL diagnostic payloads daily. The platform needed to scale ingestion throughput by 4x without dropping safety-critical fault events or breaching strict AWS budgets.

Principal Architecture & Engineering Execution

Event-Driven AWS IIoT Platform: Engineered an elastic ingestion and processing fabric across AWS IoT Core, Kinesis Data Streams, AWS Lambda, ECS, S3, and Snowflake spanning 60+ production microservices.
Snowflake Data Vault 2.0 Digital Twin Store: Designed an auditable Data Vault 2.0 model absorbing asynchronous, multi-version train sensor schemas into unified fleet health views.
Infrastructure-as-Code Standardization: Codified the entire multi-account AWS topology and CI/CD pipelines in Terraform for deterministic multi-environment promotion.

50M+ / day High-frequency IIoT sensor JSONL files processed daily

400% Scale 4x ingestion & processing capacity expansion

60+ Services Production AWS microservices orchestrated via Terraform

£1.6B Fleet Mission-critical UK rail predictive maintenance program

AWS IoT Core & Kinesis AWS Lambda & ECS Snowflake Data Vault 2.0 Terraform Python

Case Study 03 · Private Equity Carve-Out, DevSecOps & Cloud FinOps Yahoo Inc. · $5B Apollo Global M&A

Accelerating Regulated Production Releases 1,000x (6 Weeks to 6 Minutes) & Recovering ~22% Cloud Spend

During Yahoo's $5B private equity acquisition and infrastructure carve-out, strict enterprise InfoSec accreditation gates required up to 6 weeks of manual review per release, while fragmented multi-tenant cloud accounts obscured ~22% of unattributed infrastructure spend.

Principal Architecture & DevSecOps Factory

Security-Accredited Golden AMI Factory: Engineered automated HashiCorp Packer, Terraform, and Jenkins pipelines that baked CIS hardening, vulnerability scanning, and InfoSec cryptographic attestation directly into immutable machine images.
1,000x Release Acceleration: By pre-accrediting the Golden AMI build pipeline with InfoSec, production deployments dropped from 6 weeks to 6 minutes.
Cloud FinOps & Attribution Telemetry: Implemented automated cost-allocation tagging and workload rightsizing across AWS accounts, recovering ~22% in previously unattributed cloud spend.

6w → 6m 1,000x faster security-accredited production deployments

~22% Saved Unattributed AWS spend recovered via FinOps telemetry

$5B M&A Post-merger cloud carve-out & compliance separation

100% Immutable Zero configuration drift via Packer Golden AMIs

AWS EC2 / ASG / IAM HashiCorp Packer Terraform Jenkins CI/CD Cloud FinOps

Case Study 04 · Global Retail Data Modernization LC Waikiki · Global Fashion Retailer (1,000+ Stores)

Eliminating 100% of Warehouse Batch Crashes by Refactoring 15,000+ Lines of Legacy T-SQL into dbt, DuckDB & Polars

Overnight merchandising, inventory allocation, and omnichannel sales pipelines relied on more than 15,000 lines of deeply nested, undocumented T-SQL stored procedures. Deadlocks, tempdb exhaustion, and silent schema failures regularly crashed overnight batches and delayed executive retail reporting.

Principal Architecture & Refactoring Execution

Algorithmic SQL Decomposition: Parsed and refactored 15,000+ lines of monolithic T-SQL into modular, DAG-orchestrated dbt models backed by high-speed DuckDB and Polars execution engines.
Deterministic CI & Data Contracts: Introduced automated schema contracts, unit tests, and idempotent incremental materializations before any transformation reached production.
Zero-Crash Operations: Achieved 100% elimination of recurring database batch crashes while dramatically reducing compute contention.

100% Elimination of recurring overnight database crashes

15,000+ LOC Legacy T-SQL refactored into modular dbt & Polars

30%+ Faster End-to-end merchandising & BI pipeline completion

Full Lineage Column-level auditability from ERP to executive marts

dbt Core DuckDB Polars T-SQL Modernization Kimball & Data Vault

Case Study 05 · Defense, Policing & UK Public Sector Lockheed Martin (UK Met Police) & LB of Hackney

Executing an 80 TB Zero-Data-Loss Policing Intelligence Cutover & Municipal Cloud Data Platform

Mission-critical UK law enforcement intelligence systems operated under Lockheed Martin required migrating 80 TB of highly sensitive operational policing data with zero data loss and full chain-of-custody verification, alongside modernizing municipal analytics for the London Borough of Hackney.

Principal Architecture & Cutover Assurance

Cryptographic Reconciliation Pipeline: Engineered automated pre- and post-migration row-hash and payload verification across 80 TB of structured and unstructured law-enforcement archives.
Rehearsed Zero-Downtime Cutover: Executed staged dress rehearsals, delta synchronization, and deterministic cutover runbooks under UK Official-Sensitive security protocols.
Public Sector Data Lake Modernization: Unified fragmented municipal housing, finance, and citizen services datasets into governed AWS analytics pipelines for London local government.

80 TB Policing intelligence migrated with 0.00% data loss

100% Audit Chain-of-custody cryptographic row reconciliation

UK Official Delivered under strict law-enforcement security clearances

Zero Rollbacks First-time-right cutover execution across all dress rehearsals

AWS Gov / UK Official 80 TB Data Cutover Enterprise Databases Automated Reconciliation

Case Study 06 · Tier-1 Banking & Commercial Database FinOps Bank of America Merrill Lynch · Türkiye İş Bankası · Enterprise Estates

Saving >£1,000,000/yr in Commercial Database Licensing (85% Core Reduction) & Governing 200+ Banking Servers

Tier-1 investment and commercial banks run sprawling estates of hundreds of Oracle Enterprise Edition and Microsoft SQL Server instances where virtualization sprawl triggers massive per-core audit liabilities while I/O bottlenecks throttle regulatory reporting.

Principal Architecture & Licensing FinOps

Hard-Isolated Virtualization & Core Consolidation: Re-architected VMware ESXi and dedicated host cluster topologies with strict CPU affinity and storage I/O tuning, cutting licensed commercial database cores by 85% and saving >£1,000,000 per year.
200+ Server Fleet Automation: Standardized high-availability clustering, automated failover, and regulatory ETL across 200+ production database servers at Bank of America Merrill Lynch and Türkiye İş Bankası.
Sub-Millisecond Query & I/O Engineering: Eliminated storage subsystem contention so reduced-core clusters outperformed the legacy over-provisioned estate.

>£1.0M / yr Audited recurring Oracle EE licensing savings

85% Cut Reduction in billable commercial processor cores

200+ Servers Tier-1 investment & commercial banking fleet governed

SOX / PCI-DSS Full regulatory audit compliance across all environments

Oracle EE FinOps SQL Server (200+ Fleet) ESXi / Dedicated Hosts Storage I/O Tuning

Case Study 07 · Sovereign Revenue Authorities & Customs Platforms Techno Brain Group · Crown Agents

Scaling National Tax & Customs Data Platforms 19x With a 900% Transaction Throughput Boost

National revenue authorities and customs modernisation programs across emerging markets faced severe database locking and batch timeouts during statutory tax-filing peaks, threatening national revenue collection SLAs.

Principal Architecture & Throughput Engineering

Partitioned High-Concurrency Architecture: Redesigned core tax, customs, and public-finance database schemas, indexing strategies, and partitioning layouts to eliminate lock escalation.
19x Platform Scale & 900% Throughput Gain: Expanded concurrent taxpayer and customs transaction capacity by 19x while accelerating end-to-end transaction processing by 900%.
Executive Revenue Intelligence: Built automated BI and fraud-detection data warehouses giving Ministries of Finance real-time visibility into national customs and tax collections.

19x Scale Expansion in national tax & customs platform capacity

900% Boost Increase in peak concurrent transaction throughput

Sovereign National revenue & customs authority deployments

Real-Time BI Automated fraud detection & treasury dashboards

High-Concurrency DBs Table Partitioning Enterprise Data Warehousing Sovereign GovTech

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