Help us build friendly data that enables insights and machine learning across the organisation!

Pollen is on a mission to build, curate and deliver the best experiences all over the world. We want to give people a bigger life. When our members think back 10 years over their best memories, we want to be responsible for 3 of the 5 best ones.

We think we can do this by transforming the way experiences are curated and executed by evolving from art-led to science-led as we scale. Data, science and technology are at the centre of this evolution and Analytics Engineers make a critical contribution by building and maintaining an analytics friendly data ecosystem that acts as the starting place for all reporting & learning (i.e. insights and machine learning).

Analytics Engineers make it easy for Pollen to consume data. They accumulate a critical mass of expertise about our domain model, our ubiquitous language and our source system landscape and engineer a simplified data ecosystem that ties it all together in an analyst friendly way. Quality, reliability and continuous improvement are achieved through a thoughtful adoption of software development and engineering best practices (e.g. testing). All of this together gives Pollen a massive reduction in time and skill based barriers to consuming trusted data sources across the company.

In the first 12 months you will:

  • Complete the first version of a Pollen Friendly Data Design (e.g. conceptual and logical model plus ubiquitous language). Work across product and business managers, backend and data engineers, individual contributors and team leads to accumulate a critical mass of team knowledge about both our Experience domain model and how that relates to our source data landscape. Work with the team to apply this knowledge to develop a simplified conceptual and logical model, map the entities to their source system origin tables, and distill our confusing domain specific languages into a common ubiquitous language. These parts will come together to be our first data design! Success will be measured by the number of Pollen people who understand our domain model from the design and the time it takes to find data about a specific entity and resolve any confusion about its meaning.
  • Build friendly data tables for the five most consumed domain events (i.e. Fact tables) that act as the single authoritative representation of those events for across Pollen. Bring the five most needed domain events from the friendly data design to life in Snowflake by physically modelling them to complete the design process, and executing to build highly reliable data products using DBT that the entire company can rely on. Success will be measured by test coverage of the tables as well as Service Level Indicators covering Accuracy, Recency and Availability.
  • Design and implement a friendly ML-backed Customer Segmentation data set. Collaborate with Data Scientists and Engineers to design and implement a simple use Customer Segmentation table based on the complex outputs of our company wide ML-backed segmentation models. Success will be measured by the widespread inclusion of the Segmentation model in reporting and analytics products across the company, in addition to the data Service Level Indicators from above.
  • Coach and mentor other engineers in the team. Help the junior and mid engineers in the team make stretch improvements in their already strong code quality and analytical solving. Be the strongest conceptual modeller and engineer that everyone looks to for tips on how to improve their analytics engineering practices. Success will be measured by both the observable growth in the team (e.g. less time spent in code review) and the direct feedback you get from them about the positive impact you’re having on their practices.
  • Find your stretch! Analytics Engineers at Pollen own their results (e.g. those above) and from there can choose to execute upstream to work on the Data Platform, including developing ingestion pipelines in Python and scheduling on AirFlow, or execute downstream on developing reporting & analytics products (e.g. could be visualisations with d3 using Looker extensions or using basic LookML). Your stretch is completely up to you!

About our culture

About Pollen

Pollen builds, curates, and delivers the best travel experiences using technology, a network of global partners, and a data-driven customer-led mindset – pairing world class entertainment with the world’s most exciting destinations.

Pollen brings you all the best experiences on We have two offerings: Pollen Presents and Pollen+. Pollen Presents curates experiences around your tastes and preferences you can’t find anywhere else. These experiences bring together music, sports, wellness and beyond to enable you and your friends to connect around one-of-a-kind itineraries in exciting destinations. Pollen+ always gets you more at music festivals and events when you book through us. Pollen+ partners with the biggest promoter brands and music festivals, including We Are FSTVL, Austin City Limits, Bonnaroo, C3, Electric Zoo, Live Nation and more. 

Pollen was founded in 2014 by brothers Callum & Liam Negus-Fancey. Pollen is backed by prominent investors including Kindred, Northzone, Sienna Capital, Backed and Draper Spirit. Pollen has raised over $100 million in VC funding.

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Pollen’s purpose is to give people bigger lives and we want to do that for everyone. We collect this information on diversity because it is by knowing who is here, that we know who is missing – helping us drive more equitable and inclusive hiring practices.

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Diversity and inclusion is a priority for us here at Pollen and that means embracing people from all different backgrounds. 

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