As the Engineering Manager of the Events and Usage teams at Algolia, I lead the development of critical infrastructure that powers our analytics and monitoring capabilities used by our customers. I oversee the design and implementation of systems that collect, process, and analyze over 5 billion events per day, ensuring the reliability and scalability of our data pipelines.
I took over the existing Usage team in 2025, and transformed it into a high-performing and collaborative team of software engineers. Working with my Product counterpart, I delivered multiple new features to enable Algolia to become a multi-product company. I have also taken control of an existing mismanaged and years-long migration effort to move the team's data pipelines to a new architecture by restructuring the delivery plan into a series of incremental deliverables which ensured alignment with stakeholders and the team.
I built the Events team from the ground up, recruiting and hiring a team of skilled software and data engineers to take ownership of the event collection and processing infrastructure. Since taking ownership of the system in early 2026, I have led the team in delivery of new functionality to enable Algolia's agentic AI products, with a focus on customer experience and system reliability.
I established the Data Platform team in 2022, assembling a distributed team of over ten skilled software and data engineers as the hiring manager. I led the platformization of our data operations, removing the disconnection between the data engineers implementing the pipelines and their operation in production. This allowed BenchSci to deliver agentic AI solutions to our customers in a reliable and performant way.
I led the strategy behind and development of a new event-driven data platform built on Kubernetes and Pub/Sub on GCP to enable BenchSci to launch our generative AI platform for drug discovery. This sit alongside our batch processing pipeline platform based on Prefect and BigQuery.
The success of Data Platform led me to take over the AI, Search and Testing scopes in 2023. This expanded my scope to the deployment of our in house AI models and external Generative AI dependencies, the management of our persistence layer that is built on AlloyDB and Neo4j, and building our data quality and testing platform. I restructured the teams to be more aligned with the product teams they support, and continued the platformization effort to enable the data and product teams to take ownership of their end-to-end delivery.
I fostered a culture of excellence, enabling team members to achieve professional milestones through coaching and mentorship. I successfully mentor high-performing individuals, guiding them to promotions and leadership roles, while also assisting underperforming team members through performance improvement plans and candid conversations. I ensure alignment of individual career goals with company outcomes, fostering a collaborative and results-driven environment.
Led an agile team of four engineers in constructing Bloomberg's automated news platform, utilized by a team of content engineers to automatically generate news stories. Developed the product in coordination with multiple stakeholders, striking a balance between introducing new features for clients and enhancing the developer experience for content engineers. The platform was a real-time distributed system built with a combination of Python 3 and TypeScript, running hundreds of different types of automated stories triggered by market-moving events and collecting data from over one hundred data sources and APIs.
Experienced as a hiring manager for both senior and junior candidates, have conducted hundreds of interviews for different roles across the company. Specialized in interviews of candidates from diverse backgrounds outside of Computer Science.
Joined the News Automation team as a senior software engineer and led the technical direction of the team. Designed and developed the team's priority queuing system based on RabbitMQ, the story aggregation system to link similar automated stories, and many other projects.
Led the Python 2 to 3 migration of all news automation code. A 18-month project across multiple teams to migrate over 1.5 million lines of Python 2 to Python 3 without service disruption. Communicated the importance of the project with stakeholders to get it initially prioritized and to keep them engaged and informed throughout.
Coached and mentored junior members of the team, training them to lead on projects design sustainable systems.
Managed multiple clusters of Linux machines in Bloomberg's datacentres to run the team's applications, including budgeting for and provisioning hardware.
Maintained numerical models in production to predict power and gas supply and demand across Europe implemented in Python. Worked with counterparts in the product team to take their models and run them reliably in production. Built infrastructure and tooling for the models to publish their results in realtime to clients through the Bloomberg Professional Service and directly to Excel.
Wrote and maintained real time pricing engines built in C++ to publish commodity prices to clients. Pioneered migrating these from legacy big-iron systems to commodity Linux hardware.
Various software engineering roles including an internship at Bloomberg, exobiological research at the University of Edinburgh, genomic data analysis at the Insititute of Evolutionary Biology. More information available on request.
5 year master's programme in Physics specialising in computational and macromolecular physics. Master's dissertation in modelling bacterial growth on rocks. Bachelor's dissertation on factor analysis of data analysis skills of physics students.