Analytics Engineering Manager

Description:

Lead, develop and be a part of a growing team of Analytics Engineers overcoming the unique data challenges that come from building a new category with a real world product (i.e. curated travel experiences).

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 transform the way experiences are curated and executed by evolving the craft from art-led to science-led and achieving unprecedented scale. Data, science and technology are at the centre of this evolution and this role will lead the Analytics Engineers who make a critical contribution by building and maintaining an analytics friendly data ecosystem that acts as the starting place for all self-service reporting & learning (i.e. insights and machine learning).

Leaders at Pollen are the people who create the space for others to succeed. They partner across the organisation to build teams, develop individuals and inspire others to play to their strengths as they contribute to Pollen's mission. They work with the People team, and functional leads, to ensure we're delivering our employment promise of Freedom & Ownership, Mastery and Belonging. They proactively surface the data barriers that keep us from achieving our mission, clearly articulate them before taking ownership of (or advocating for) how we overcome them.

The Analytics Engineering Manager role in particular is one where mastery in leadership is combined with seasoned analytical and software engineering practices to help build scientific capacity within our organisation. As a result of their actions and direction, everyone at Pollen is better equipped to use data to observe, understand, predict and influence our performance.

What you'll do in the next 12 months

• • Minimise time, skill and knowledge based barriers to consuming data for analysts and end users, enabling self-service data experiences across Pollen.
    • Collaborate across domain experts, Data Engineering, Analytics & Data Science to design and lead the team to build user friendly, accurate, documented and reliable datasets for analysts and end users to launch into their work.
    • Success will be measured in the minutes spent by data consumers preparing the data and clarifying it's meaning before using it (e.g. for operations, reporting and insights)
  • Ensure data is created with quality, integrity and completeness at source.
    • Work upstream to create a space where analytics engineers and product & system engineers can collaborate to make improvements to their data modelling and data creation standards.
    • Success will be measured by the number of product teams who are clear about their data creation requirements to enable self-service learning at Pollen.

• Be like Yoda!

• Primarily lead by mentoring, supporting and activating through others but elevate the team's work by introducing engineering & data modelling best practises, enabling the team to improve efficiency and otherwise empowering them to get going (and then get better).

• Success will be measured in the release velocity of datasets and the reliability of the them (e.g. accuracy and recency).

• Continuously surface data team barriers and help us evolve to overcome them.

• • Move the data organisation towards high performance by working with the Director of Analytics and Data Science to surface issues affecting team motivation and impact, or process/tooling challenges, which are hindering the team's progress.
  • Success will be measured by the absence of recurring themes for improvement in team retros.
• Empower, develop and build community in the team.
  • Develop a skilled, motivated Analytics Engineering team, by retaining a highly engaged and passionate group and maintaining a sense of belonging.
  • Success will be measured by the number of team members who are still at Pollen after 12 months.