Hi, I’m Pablo.

I solve problems with technology, data and AI. An aerospace engineer by training, a data leader by trade, and a builder by habit.

Over eleven years in aviation, health tech and legal tech, I’ve built data teams from scratch, shipped apps people use, and lately put AI agents to work. Today I lead Engineering & Maintenance data at British Airways, and I’m open to projects on the side.

Open to new projects · Based in London

Things I’ve built

Side projects I build to learn by doing. Both are live.

Airline Intelligence

A research team that never sleeps.

Seven Claude agents that read airline filings and turned them into more than 1,600 sourced, audited figures, with a mission-control panel tracking every run and what it cost.

Claude Agent SDK · MCP · Next.js · Firestore · Google Cloud

Code on GitHub

Rave Recall

London's club nights, and who's going.

A no-sign-up companion for London club nights: a chat room for every club, a city-wide board of who’s going where, and private messages. Designed for 4am, on a phone, in the dark.

React · Firebase · MapLibre · PostHog

How I can help

Problems rarely arrive labelled “data” or “AI”. They arrive as something slow, manual or unclear. Because I work across all of it, I can pick the simplest fix and build it myself.

  • Connect your data

    Pipelines, warehouses and models that turn data scattered across tools into one source of truth people trust.

  • Build tools people use

    Dashboards, internal apps and interfaces shaped around how your team really works.

  • Put AI agents to work

    Agents that research, extract, report and automate, with checks built in so you can trust what they hand back.

  • Set up a data function

    Strategy, KPIs, hiring and ways of working. I’ve built one from zero twice, at venture-backed startups.

Experience

From planning airline routes to leading data teams, at British Airways and at venture-backed startups, hands-on throughout.

  1. British Airways Engineering & Maintenance

    2026 – now

    Senior Product Area Manager

    Leading a team of eight data scientists and engineers across all of the airline’s engineering and maintenance data.

    Highlights
    • Made dbt the standard, so the whole domain works from one trusted source of truth
    • Designed an AI-ready reporting layer that lets people ask questions in plain English through Snowflake AI Agents
    • Brought AI-assisted coding into the team, cutting the time to build a data model by 60%
  2. Lawhive Legal tech AI · Series B

    2025 – 2026

    Lead, acting Head of Data

    First data hire. Built the function from zero and was promoted to lead it after seven months.

    Highlights
    • The C-suite’s main data contact, and ran the data room for the Series B
    • Created the company’s first KPI framework and unit economics (LTV, CAC)
    • Led the data side of the US launch and of integrating an acquired law firm
  3. Mojo Mental health AI · Seed

    2024 – 2025

    Lead Analytics Engineer

    Led data engineering and analytics at a startup building an AI therapist.

    Highlights
    • A machine-learning model that lifted revenue per user by 10% in some cohorts
    • A tool for human therapists to review high-risk conversations with the AI, making it safer
  4. Bumble Dating apps

    2021 – 2024

    Senior Data Scientist, then Full Stack Senior Data Analyst

    Data science for growth, then a move into backend engineering for Bumble Studio’s new prototypes.

    Highlights
    • A budget-allocation model that halved cost per acquisition in smaller markets
    • Productive in Go within a month, owning a core part of a new app’s backend and making its endpoints 70% faster
    • Personalised push notifications that doubled active users
  5. British Airways Digital & Commercial

    2018 – 2021

    Data Science Manager

    Promoted from analyst within six months to build a new team of four.

    Highlights
    • Twice received the Above and Beyond award from the Chief Commercial Officer
    • Found the bug on ba.com’s payment page that was blocking some payments, by analysing customer feedback
  6. Amadeus & Iberia Airline technology & strategy

    2015 – 2017

    Implementation Engineer · Network Strategy

    Implemented reservation systems for airlines, and before that planned Iberia’s routes: a demand model raised the profitability of some summer flights by 50%.

Kind words

“Pablo goes above and beyond constantly. I have never seen someone so dedicated, especially in the face of so many competing priorities. He acts with professionalism and dignity while under considerable pressure, and finds ways to help even when there are seemingly not enough hours in the day to do so. And he always acts with kindness, caring so much about the work and the relationships he is building across the business. We need more people like Pablo.”

VP of Marketing at Lawhive · formerly CMO at Fresha

“All we can do at the data team is thanks to his leadership, composure and incredible work ethic. Pablo is the most hands-on lead I’ve seen in my career. He is on top of details and can manage to keep a coherent data strategy under enormous pressure that would make anybody else cut corners. On top of that he is managing to do this without losing his human side, his smile and his empathy.”

Software Engineer at Lawhive · 25 years’ experience

Talks and training

Speaking and teaching

  • 2026Using dbt with AI Agentsdbt London Meetup
  • 2026Building a Data Function in the Age of AIData Engineering Meetup, hosted by Orchestra, Tracer and Lightdash
  • 2024Taught more than 90 students software engineeringTech Summer School
  • 2021Post-Covid Dating, and How to Create an AI-First OrganisationAI Summit London, two talks

Education

  • MSc Air Transport SystemsPolytechnic University of Madrid
  • Bachelor’s in Aerospace EngineeringPolytechnic University of Valencia
  • Bachelor of PianoConservatoire of Valencia
  • Machine Learning and Artificial IntelligenceStanford, online

Toolbox

Data
SQL, dbt, Snowflake, BigQuery, Python, Airflow, Dagster, Fivetran, Looker, Hex, Lightdash
AI
Claude Code, Anthropic API, Claude Agent SDK, MCP, Snowflake Cortex, Vertex AI, LangGraph, n8n
Software
TypeScript, React, Next.js, Go, Firebase, Google Cloud, Docker, Kubernetes, GitHub Actions

Let’s work together

Tell me what’s slow, manual or unclear, and what “fixed” would look like. You don’t need to know whether it’s a data, software or AI problem; working that out is part of the job.

Or reach me at pablofergui@gmail.com or on LinkedIn.