Senior Data Engineer and Data Platform Architect with over 8 years of experience building high-scale, production-grade infrastructure at the intersection of Data Engineering, Applied AI, and Cloud Architecture. Working across fast-paced environments in Health-Tech, Global E-commerce, and Enterprise AdTech, my career has been defined by a single principle: data platforms should not just pipeline data—they should actively protect and generate business revenue.

Over nearly a decade of engineering, my expertise has evolved alongside the data landscape. I specialise in designing robust data lake architectures (utilising Google BigQuery and Snowflake), modeling and transforming complex datasets with DBT, and engineering secure, global vendor-provisioning frameworks via custom APIs and Looker ecosystems.

Where I bring distinct competitive value is my ability to bridge the gap between traditional data engineering and modern AI infrastructure. Whether architecting real-time personalisation pipelines for machine learning models or deploying tailored RAG (Retrieval-Augmented Generation) internal applications to safeguard code deployments, I build the core systems required to scale intelligent data products. I thrive in high-velocity, "AI-first" environments where ownership means taking a project from raw ingestion to live product delivery, empowering stakeholders to self-serve, and moving the financial needle.

MALTBY TECH

Python
SQL
GCP
HTML
GitHub
Modelling
ETL
Agile
Coaching
Dashboards
Applied AI

History

  • A high-velocity, three-month position focused on facilitating rapid development within an AI-first environment. I took end-to-end ownership of high-impact data pipelines while simultaneously defining and accelerating the team's engineering delivery rate.

    Key Contributions:

    • Revenue Protection: Engineered a business-critical pipeline with an ultra-fast production turnaround, plugging a live financial leakage point to secure six-figure annual revenue.

    • Data Democracy: Designed and deployed scalable data structures that better enabled non-technical business stakeholders to confidently self-serve data.

  • A remote position focused on bridging the gap between large-scale cloud infrastructure and global product impact. I took technical ownership of complex platform migrations and engineering lifecycles, establishing modern team workflows to elevate platform uptime and system resilience.

    Key Contributions:

    • Stack Modernisation & Governance: Directed the large-scale migration of legacy marketing ETL systems into a clean, modern Python, dbt, and Airflow system, successfully boosting global platform availability.

    • Data Integrity & Debugging: Identified and resolved long-standing synchronisation anomalies, completely eliminating duplicate conversion data from critical offline data feeds to restore absolute baseline truth to downstream performance marketing attribution models.

    • ML Personalisation Pipelines: Collaborated closely with internal machine learning teams to build robust production pipelines that piped real-time user intent markers into dynamic landing pages, drastically optimising user retention journeys and marketing ad quality scores.

  • A multi-faceted engineering leadership role focused on architecting proprietary software products, building secure enterprise data lakes, and managing cross-functional technical teams. I served as the core architect for global brand data infrastructure, directly moving the commercial needle through automated algorithmic solutions.

    Key Contributions:

    • Global Vendor Provisioning: Managed the core architecture, data formatting, and governance for hundreds of Looker dashboards distributed to external partners. Utilised Google BigQuery as an enterprise data lake, leveraging Funnel.io and custom Python API pipelines to securely ingest, model, transform, and programmatically deliver clean data products to vendors globally under strict row-level access permissions.

    • Proprietary Product Engineering: Scaled a manual prototype into an enterprise-grade SaaS analytics application ("Onesearch"). Built the final production architecture on GCP, utilizing Apache Airflow to orchestrate web scraping networks and programmatic ad mutations via external APIs to generate six-figure standalone revenue.

    • Algorithmic Inventions: Ideated and engineered an automated top-of-funnel bidding solution ("Attention Maximiser") that dynamically analysed historic consumer datasets to construct bespoke bidding logic, delivering a massive improvement in campaign CPM at near-zero infrastructure cost.

    • Technical Leadership & DevOps: Managed a multi-tiered international engineering network across direct reports and external partner agencies. Introduced modern engineering hygiene by building the department's first internal GitLab architecture from scratch, configuring all automated validation environments and CI/CD deployment pipelines.

  • Working as a full stack developer (Python, Django, HTML, JS) to develop legal software. Working initially as one of two developers, I created the chat system, contract creation tools, the 2FA authentication systems and contributed more broadly to the wider codebase.

  • Exclusively working with Samsung UK, my role was to extract, transform and visualize insights for UK mobile sales from marketing campaigns. I created the teams first ETL pipeline which replaced hours o manual updates while simultaneously delivering more frequent data updates. I also built forecasting tools to empower non-digital channels through digital.

  • Initially working with WeShop as their first employee as an intern during my summers while studying. I was hired full time as an analyst after graduation. I had a very broad remit working in this start-up that saw me slowly apply more and more engineering to my role as I learnt it in my free time.