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Feature delivery and product planning on new and existing BBC products, inside an account team of around eight.

Tens of millionsaudience for the BBC products the team delivered features on
~8people in the account team
The situation

The BBC's work was held by an agency, which ran an account team of around eight across products already live and products still being built. We joined that team at senior engineer level in 2023.

The brief covered feature work and the planning that sits in front of it, so we were in product and engineering discussions as well as writing code. Our record does not name which BBC products.

The constraint

Reach is the constraint the CV states. The audience for these products is in the tens of millions, which sets both the cost of a bad release and the size of the regression surface.

Eight people covering new build and existing products is the other half of it, because the same small group carries maintenance and new features. The technology list for the engagement includes Optimizely alongside Node.js, React, Redux and Jest. The CV does not say which products were new and which were already live.

What we did

We held a key seat on that account team, delivering features on new and existing BBC products and contributing to product and engineering planning alongside that delivery.

The stack was Node.js on the server, React with Redux and React Context on the client, Jest for tests, Docker and Bash around the build, and GitHub with JIRA for the workflow.

The outcome

Features shipped on BBC products reaching an audience in the tens of millions, from inside an account team of around eight.

The CV records no release counts and no product performance figures, and it does not name the products. The audience number and the team size are what the source supports.

Stack
  • Node.js
  • Docker
  • Jest
  • Bash
  • Optimizely
  • React
  • Redux
  • React Context
  • Git
  • GitHub
  • JIRA
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