🚀 Senior Data & AI Platform Engineer | AWS, Snowflake, dbt, Azure

10+ years building enterprise cloud data platforms across regulated financial services and investment management. I combine architecture depth with hands-on delivery — personally shipping production pipelines, dbt models, and governance frameworks — while leading teams, aligning stakeholders, and driving platform strategy at increasing scope and seniority within investment management and regulated finance.

• Architecting governed lakehouse platforms using medallion architecture, Dagster, and dbt.
• Designing cloud-native data solutions across AWS, Azure, Snowflake, and Databricks.
• Building AI-ready data platforms with LLMs, RAG, Snowflake Cortex, and AWS Bedrock.
• Establishing data governance — contracts, schema evolution, lineage, observability, and RBAC.
• Building and leading data teams, from first hire through domain-oriented, multi-engineer functions.

Programming & Query Languages:

Cloud & Data Platforms:

Data & Transformation Tools:

AI & LLM:

Development & Infrastructure:

• Architected a governed medallion lakehouse and Dagster orchestration platform, cutting new source-system connector delivery from 3–5 months to 2–3 weeks.
• Designed and shipped production Python and dbt data products with schema validation, contracts, lineage, and automated testing across multiple enterprise platforms.
• Built and led a data function from 7 to 22 engineers, establishing roles, career paths, standards, and domain-oriented delivery.
• Delivered CI/CD modernisation and GitFlow adoption across a 249-repo estate, unblocking a stalled release process and raising platform engineering maturity.
• Delivered enterprise AWS, Azure, and Snowflake lakehouse platforms with RBAC, classification, and audit-ready governance across investment management, banking, lending, and energy.

• AI-driven data pipelines combining Snowflake Cortex, RAG, and LLMs for AI-ready platforms.
• Data contracts and observability (freshness monitoring, volume checks) for Snowflake-backed data products.
• CI/CD and engineering standards — pre-commit hooks, linting, and branch protection across data platform repos.

• github-trend-insights 📊 – Data pipeline analyzing GitHub trends using dlt, DuckDB, and dbt.
• agile-ai ⭐ – AI-powered agile project management tools.

• 💼 LinkedIn
• 📧 Email
• 🏗 GitHub
• 📝 Personal Blog (archives of data engineering insights)