Octopus Deploy sets the standard for Continuous Delivery, empowering software teams to deliver value in an agile way. Over 4,000 organizations globally – including Ubisoft, Xero, Stack Overflow, NASA, and Disney – rely on our Continuous Delivery, GitOps, and release orchestration solutions.
If you join Octopus, you’ll become a part of a high-trust, remote-first, and value-driven culture.
Overview
The Product Growth team at Octopus Deploy relies on data to understand how customers discover, try, buy, and succeed with our products. Our mission is to make those signals clear, trustworthy, and actionable, so teams across Octopus can make better decisions with confidence.
Octopus is scaling to serve thousands more customers across multiple products and journeys, and the questions we ask of our data are becoming more complex. We already have strong data engineering foundations in place. This role exists to ensure that data is explored, interpreted, and communicated in ways that meaningfully influence product, growth, and business outcomes.
As an Analytics Engineer at Octopus, you’ll build reports, dashboards, and forecasting models that inform product and business decisions. You’ll collaborate with engineers, product managers, and finance to structure data, identify trends, and forecast customer behaviour, while developing strong data modelling and analytical skills in a team that values clarity and curiosity.
If you enjoy finding patterns in data, telling clear stories with evidence, and helping teams move faster with better information, we’d love to hear from you.
This is a remote role based in Australia or New Zealand. We work asynchronously by default, with a strong emphasis on clear written communication, documentation, and thoughtful collaboration across time zones.
What you’ll do
Explore datasets to identify trends, patterns, and anomalies across the customer lifecycle.
Analyse data to answer more complex product, growth, and business questions.
Present findings clearly, focusing on the story behind the data and what it means for decision-making.
Partner with product managers, engineers, and other teams to refine questions and iterate on insights.
Build dashboards and reports that surface trusted metrics and enable product, finance, and growth teams to explore data with confidence.
Build reusable analytical models that support consistent reporting and repeatable analysis.
Work closely with data engineers to understand data models, definitions, and data quality constraints.
Document data definitions, table structures, and common analysis patterns.
What you’ll bring
Experience working with SQL to query and analyse real-world datasets.
Working knowledge of Python (Pandas or similar), for analysis and modelling.
Experience building or contributing to dashboards and visualisations.
A clear, practical understanding of basic data modelling concepts, such as fact tables, dimension tables, and star schemas.
Demonstrated ability to communicate analytical findings clearly to both technical and non-technical audiences.
Motivation to help others succeed with data, not just complete tickets or deliver reports.
Confidence working independently on well-scoped analysis, with good judgement about when to ask for help.
Curiosity, a learning mindset, and an interest in how data informs product and business decisions.
Nice to have
Experience working with Snowflake or other modern cloud data warehouses.
Familiarity with dbt or similar tools for building and maintaining analytical models.
Exposure to data ingestion or ELT tools such as Estuary or Fivetran.
Experience working with product, growth, or commercial data in a SaaS environment.
An interest in experimentation, attribution, or forecasting use cases.
Why join this team
Impact: Your work will directly influence how Octopus understands its customers and drives revenue, helping teams decide what to build next.
Learning: You’ll deepen your analytical skills while working alongside experienced data engineers and product teams, gaining exposure to both product growth, and commercial domains.
Growth: This is a new and growing capability at Octopus. As our use of data evolves, so will the scope and impact of your role.
Collaboration: You’ll work with a wide range of teams and disciplines across the company, helping connect data to real outcomes.
Why Octopus
Octopus has been remote-first since 2015 and works with an uncommon level of transparency. You can read our public handbook to learn how we work. We have a transparent approach to compensation that ensures people doing the same work with the same skill get paid the same, with well-defined career pathways. We foster a supportive, collaborative, and high-trust environment. We leave our job titles at the door and focus on doing what’s best for our customers and team. Our leaders never shy away from answering the tough questions at our all-hands calls or in 1:1s. We conduct interviews and onboarding virtually as part of being a remote-first company.
Compensation:
The compensation for this role is:
Level 2 (Intermediate): Maturing: $115k AUD / $125k NZD, Performing: $135k AUD / $145k NZD
Salaries exclude Super and KiwiSaver.
Benefits include a minimum of 25 days annual leave, up to 10 days of paid sick and carers leave, 12 weeks of fully paid parental leave with flexible return options, and stock options. Learn more.
Below is the interview process you can expect for this role. We know interviewing can seem daunting, but rest assured we designed our interview process to move quickly while still getting you all the information you need.
👋🏼Initial chat
[30 min] Talent acquisition screen: Meet with your Talent Acquisition team and get a feel for what it would be like to be an Octonaut!
☕ Technical Interview
[2-4 hours] We’ll discuss your past analytical work, including how you approach questions, explore data, and interpret results. We’ll also cover how you communicate insights, reason about trade-offs or data limitations, and collaboration with others to turn analysis into decisions.
🧑💻Values interview
[45-60 min] Focus on how you work within a team, including communication style, collaboration with product and engineering partners, and approaches to learning and feedback. We’ll also explore how they handle ambiguity, manage priorities, and contribute positively to team culture in a remote, asynchronous environment.
