Analytics Engineer

Analytics Engineer

Full-Time 40000 - 50000 ÂŁ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Build and maintain data models, create dashboards, and tell compelling data stories.
  • Company: Join a fast-growing outdoor brand passionate about escapism and sustainability.
  • Benefits: Enjoy flexible hours, generous leave, private medical insurance, and a supportive culture.
  • Other info: Collaborative team environment with opportunities for personal and professional growth.
  • Why this job: Make a real impact by transforming data into insights that drive business decisions.
  • Qualifications: Experience with BI tools, SQL, and a passion for innovation and AI.

The predicted salary is between 40000 - 50000 ÂŁ per year.

Who We Are

Passenger is driven by a passion for escapism, connection, and the wellbeing of both people and the planet. As a fast‑growing brand in the outdoor sector, we create products that are 'made to roam' and embody a culture that embraces inclusivity and fosters a collaborative team environment. We’re looking for someone who shares our passion for protecting the planet while building something unique and authentic.

Overview

An opportunity has arisen for an Analytics Engineer to join our data team. You’ll be responsible for building and maintaining the data transformation layer that powers analytics across Passenger, while creating compelling visualisations and insights that drive business decisions. Working closely with our Head of BI and Data, you’ll translate business logic into robust dbt models and bring data to life through self‑service dashboards and data storytelling in Lightdash. This role uniquely blends technical data engineering with business intelligence; you’ll need to be as comfortable writing SQL and building dbt models as you are crafting dashboards and presenting insights to stakeholders. Your role will bridge the gap between raw data and business impact, building scalable data models that enable teams across the business to make data‑driven decisions, while also being the person who helps them understand what the data is telling them. We are always looking for the next edge, and we want someone who brings a genuine appetite for innovation and AI, so we can keep punching above our weight as a lean data team.

What You’ll Be Doing Day To Day

  • Build the transformation layer: create and maintain dbt models that transform raw e‑commerce data into analytics‑ready datasets across customer, product, marketing, finance and operations domains.
  • Tell data stories: design and build intuitive dashboards and visualisations in BI that answer business questions and surface insights proactively.
  • Partner with the business: collaborate with teams across trade, marketing, finance, product, and operations to understand their needs and deliver analytical solutions that drive decisions.
  • Write production‑quality SQL: build clean, well‑tested, documented queries in dbt that adhere to data quality standards.
  • Communicate insights: present complex data findings in clear, compelling ways to both technical and non‑technical audiences.
  • Maintain documentation: keep data models, metrics, and dashboards well‑documented within dbt and our BI platform.
  • Experiment and innovate: actively experiment with new AI tools and techniques, sharing learnings with the wider team to raise the bar on how we work with data.
  • Support ad‑hoc analysis and exploratory work on business projects.
  • Leverage AI to support relevant research and analysis tasks.

What You Will Bring

  • Strong foundation and experience using BI and visualisation tools such as Lightdash/Looker or similar (Power BI, Tableau, etc.).
  • Strong foundation and experience using dbt and knowledge of its core concepts and best practices.
  • Well versed in database management tools and data structures, understanding of SQL & JSON.
  • Familiar with data warehouse technologies such as BigQuery, Snowflake.
  • Familiar with ELT and ETL processes and data pipeline orchestration.
  • Familiarity with automation platforms like N8N or Make.
  • Strong interest and a keen drive to proactively embrace the use of AI for co‑working and co‑pilot functionalities to enhance your role and productivity.
  • Strong analytical and problem‑solving skills.
  • Strong Excel/Google Sheets skills.
  • Ability to manage multiple projects simultaneously.
  • 2+ years of experience as an Analytics Engineer, Data Analyst, or BI developer.
  • Understanding of key e‑commerce data models and concepts is desirable.

What We Offer

We nurture and empower the whole you – mind, body, and spirit. Our rewards package is designed to fuel your passions, support your ambitions, and cultivate an environment where you can thrive. In addition to a competitive salary it includes:

  • A culture of empowerment, freedom, flexibility, and trust.
  • Escapism is serious business for us. We practise what we preach and connect together for quarterly in‑person cabin sessions and getting outside.
  • Our HQ is in the New Forest, 5 minutes from the sea.
  • Typical hours: 8.30am - 5.30pm, 5 days a week.
  • Annual leave: 25 days plus bank holidays + a day for your birthday.
  • Very generous staff discount and friends and family discount.
  • Private medical insurance for you and your dependants.
  • Enhanced pension contributions.
  • Annual volunteering day to support causes that matter to you.

Equal Employment Opportunity

All qualified applicants will receive consideration for employment without discrimination on the basis of race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or any other factors. Any applicant that believes they need reasonable accommodations to perform the duties of this role is invited to discuss this with us and let us know in your application.

Analytics Engineer employer: Passenger

Passenger is an exceptional employer that champions a culture of empowerment, flexibility, and inclusivity, making it an ideal place for an Analytics Engineer to thrive. With a focus on personal and professional growth, employees enjoy generous benefits including 25 days of annual leave, private medical insurance, and opportunities for community engagement through volunteering. Located in the picturesque New Forest, just minutes from the sea, the company fosters a collaborative environment where innovation and passion for the planet are at the forefront of its mission.
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Contact Detail:

Passenger Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Analytics Engineer

✨Tip Number 1

Network like a pro! Reach out to people in the industry, especially those at Passenger or similar companies. A friendly chat can open doors that a CV just can't.

✨Tip Number 2

Show off your skills! Create a portfolio of your best data visualisations and projects. When you get the chance, share it during interviews to demonstrate your expertise.

✨Tip Number 3

Prepare for the interview by understanding Passenger's mission and values. Be ready to discuss how your passion for the planet aligns with their goals – it’ll show you’re a great fit!

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step.

We think you need these skills to ace Analytics Engineer

SQL
dbt
Data Visualisation
Lightdash
Business Intelligence
Data Storytelling
Data Modelling
E-commerce Data Models
BigQuery
Snowflake
ETL Processes
ELT Processes
Automation Platforms
Analytical Skills
Problem-Solving Skills
Excel

Some tips for your application 🫡

Show Your Passion: When writing your application, let your passion for data and the outdoors shine through. We love candidates who share our enthusiasm for protecting the planet and creating something unique!

Tailor Your Experience: Make sure to highlight your relevant experience with BI tools, SQL, and dbt models. We want to see how your skills can bridge the gap between raw data and impactful business decisions.

Be Clear and Compelling: Communicate your insights in a way that’s easy to understand. Remember, you’ll be presenting to both technical and non-technical audiences, so clarity is key!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and get to know you better. Don’t miss out on this opportunity!

How to prepare for a job interview at Passenger

✨Know Your Data Tools

Make sure you’re well-versed in the BI and visualisation tools mentioned in the job description, like Lightdash or Looker. Brush up on your dbt skills too, as you'll need to demonstrate your ability to create and maintain robust data models.

✨Craft Your Data Stories

Prepare to showcase how you can turn raw data into compelling insights. Think of examples where you've designed intuitive dashboards or visualisations that answered key business questions. Be ready to explain your thought process behind these creations.

✨Communicate Clearly

Practice presenting complex data findings in a way that’s easy for both technical and non-technical audiences to understand. You might want to prepare a mini-presentation or a case study to illustrate your communication skills during the interview.

✨Show Your Passion for Innovation

Passenger is looking for someone who embraces innovation and AI. Be prepared to discuss any new tools or techniques you've experimented with in your previous roles. Share your thoughts on how these could enhance data processes and decision-making.

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