Enterprise Data & AI · Financial Services and beyond
Data & AI Engineer | Solution Architect | Cloud | MLOps
I help companies at enterprise-grade level turn complex data estates into secure, production-grade data & AI platforms across Azure and Google Cloud.
I am a Data & AI Solutions Engineer with experience delivering enterprise-scale data & AI initiatives across Azure and Google Cloud. I work with data at cloud platforms since 2019 with data engineering expertise. Since August 2024, my work has spanned data monetization platforms, generative AI / LLM and agentic solutions, MLOps and production ML, FinOps and governance, and competitive pre-sales, built on Azure Databricks, Microsoft Fabric and Microsoft Foundry. Earlier at Thoughtworks, I designed near-real-time airline and retail data platforms that deepened my foundations in CDC, distributed systems and event-driven architecture. Every initiative emphasizes secure architecture, governance & compliance (Microsoft Purview, Entra ID, RLS/CLS) and production readiness (scalable design, monitoring, drift detection, FinOps), delivered through close cross-team collaboration.
I translate ambiguous business goals into reference architectures and working solutions that survive production. I am equally comfortable designing a federated data mesh, fine-tuning an LLM, standing up an MLOps pipeline, or leading a competitive proof-of-concept under deadline.
My engagements pair technical depth with clear storytelling: I build the demo, draw the architecture, run the workshop, and write the proposal—then package the result as a reusable accelerator so the value scales beyond a single customer.
A snapshot of the platforms, frameworks and practices I use to deliver enterprise data & AI solutions.
25 selected engagements, summarized here and documented in full on their own page using the STARL method (Situation, Tasks, Actions, Results, Lessons Learned). Client identities are anonymized by sector. Use the index, filters or search to navigate.
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Federated data mesh, reference blueprints and cross-platform governance.
Role: Lead Solution Engineer / Architect
Designed and led a proof-of-concept for a federated data mesh that lets a capital-markets client securely monetize curated market data as products—combining Fabric/OneLake domains, Databricks engineering, embedded Power BI and an AI multi-agent query layer.
Role: Solution Engineer / Field Lead
Defined and evangelized “Better Together” reference architectures that integrate Azure Databricks and Microsoft Fabric—shifting client conversations from “vs” to “and” and unlocking new Fabric workloads atop existing Databricks lakehouses.
Role: Architect / Author
Authored an enterprise Azure Data Mesh reference architecture—domain-oriented data products, federated governance and security—reused as a repeatable blueprint across multiple FSI engagements.
Role: Governance Solution Engineer
Integrated Microsoft Purview with Azure Databricks and Microsoft Fabric to deliver a unified catalog, cross-platform masking and an Entra ID-based access model—giving a financial-services client a single governance pane.
Role: Cloud Solutions Architect
Assessed and redesigned a major airline's first modern Google Cloud data platform, replacing a fragile custom-CDC direction with a managed-CDC decision path and a scalable, event-driven Data Mesh architecture for reliable near-real-time analytics.
Role: Data Solutions Engineer
Designed and delivered an Azure-native fulfillment data platform for smart shopping-trolley telemetry and product master data, using custom streaming controls to achieve reliable near-real-time operations without Databricks.
Fine-tuned LLMs, RAG/GraphRAG, multi-agent systems and enablement.
Role: Solution Engineer / ML Lead
Fine-tuned a GPT-4.1 model and built a multi-agent NL2SQL system that lets business users query Databricks, Fabric, SQL and Oracle in natural language—reaching ~85% SQL accuracy.
Role: Solution Engineer / AI Architect
Delivered a secure GraphRAG assistant over contracts and knowledge bases using Postgres/pgvector retrieval, GPT-4, Fabric Data Agent and Foundry—answering complex questions with clause-level citations in under five seconds.
Role: Instructor / Author
Designed and delivered a hands-on workshop on building and fine-tuning LLMs/SLMs on Azure (Databricks + Fabric)—enabling colleagues and partners to start their own domain-specific LLM proofs-of-concept.
Role: Solution Engineer / Prototyper
Prototyped an AI persona framework using multi-agent LLM simulations to generate synthetic customer personas and stress-test new product concepts before costly market research.
Production ML pipelines, model comparison and platform evaluation.
Role: MLOps Solution Engineer
Built an end-to-end MLOps pipeline on Azure Databricks to productionize a PyTorch fraud-detection model with Feature Store, real-time serving and drift monitoring—cutting deployment time from months to weeks.
Role: Solution Engineer / Data Scientist
Ran a head-to-head AutoML vs custom-PyTorch churn study on Azure ML with MLflow tracking and SHAP explainability; AutoML won (AUC 0.88 vs 0.84) and was deployed as a scoring endpoint.
Role: Pre-Sales Solution Engineer
Created demos and prototypes proving end-to-end PyTorch ML workflows on Microsoft Fabric, clarifying Fabric vs Databricks positioning for FSI clients evaluating Fabric as an ML platform.
Cloud cost intelligence and infrastructure governance.
Role: Solution Engineer / FinOps
Built a Fabric-based FinOps solution that ingests Azure cost data, models it to the FOCUS standard, and surfaces reservation coverage and forecasts in Power BI—driving smarter reservation purchases.
Role: Advisory Solution Engineer
Designed and implemented automated IaC drift detection that compares deployed Azure resources to Terraform/Bicep state and alerts on drift via Teams and email—improving the client's compliance posture.
Competitive PoCs, RFP/RFI, partners and reusable accelerators.
Role: Competitive Solution Engineer
Led competitive Power BI + Fabric PoCs that reimplemented Tableau dashboards on the client's data—cutting report load times ~40% and adding Copilot natural-language Q&A—moving clients to pilot a Tableau-to-Power BI transition.
Role: Competitive Solution Engineer
Crafted competitive target architectures and value narratives positioning the Azure data & AI stack against AWS and GCP—contributing to competitive wins and shortlists in FSI and public-sector pursuits.
Role: Solution Architect (Bid Support)
Drove the architecture and technical-writing portions of major RFP/RFI responses—designing solution architectures, building cost estimates, and writing proposals that advanced bids to final stages.
Role: Technical Lead / Partner Manager
Managed and integrated partners and ISVs across enterprise delivery—onboarding them to Azure reference patterns and acting as a quality gate to deliver seamless, on-time customer outcomes.
Role: Solution Engineer
Continuously delivered tailored demos, PoCs, pilots and reusable accelerators across Azure Data & AI—progressing deals and creating assets reused by colleagues across regions.
FIAP course authorship, curated learning resources and personal open-source tools built outside client engagements.
Role: Course Author / Instructor
Authored an 8-class graduate course on detecting, monitoring and mitigating data and concept drift in production ML systems, for FIAP's postgraduate Machine Learning Engineering program.
Role: Course Author / Instructor
Authored an 8-class course teaching data scientists the software-engineering practices — version control, testing, containers, dependency management, code quality and CI/CD — needed to ship reliable, production-ready code.
Role: Course Author / Instructor
Authored an 8-class graduate course on securing LLM-based systems — threats, guardrails, data protection, red teaming, LGPD/GDPR/EU AI Act compliance, LLMOps observability, fairness and secure production deployment — anchored on a fictional banking assistant.
Role: Creator & Maintainer
Built a curated, community-sourced hub of learning references and a study-project scaffold spanning the Data Analytics, Data Engineering, Data Science, ML Engineering and AI Engineering tracks.
Role: Creator & Maintainer
Built an experimental, stateless reverse-proxy gateway that exposes an Entra-only Microsoft Foundry deployment as an OpenAI-compatible endpoint, so any OpenAI-SDK-compatible client can use it without ever handling Entra tokens or a Foundry API key.
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