Senior Analytics Engineer

We are committed to promoting a diverse and inclusive workplace - a place where we can each be ourselves and do the best work of our lives. At Tracksuit we consider a unique perspective, diverse experience and a growth mindset to be of greater value than ticking every box on a JD. If you think you have what it takes but don’t have the exact experience we’ve set out, please still get in touch and apply. We’d love to chat!

At Tracksuit we provide beautiful, radically affordable, always-on brand tracking which is easy to use compared to traditional methods. We recognise that sounds like a ton of buzzwords for marketers, so what it really means is that we did over tens of thousands of surveys last month to find out what real humans think and feel about the world’s best brands and their competitors. Check us out here 🙌

Are you our new Senior Analytics Engineer?

At Tracksuit, data isn't a back-office function — it's the backbone of every decision we make. In this role, you'll build and evolve the internal analytics platform that powers our Product, Finance, and GTM teams (Customer Success, Sales, and Marketing) across our growing global organisation.

You'll work closely with Data Engineers, Data Analysts, Software Engineers, Product Managers, and Operations colleagues across our international offices, shaping the quality and strategic direction of our internal data capabilities at scale.

👉 Please note: This role can be based in either our Auckland or Sydney office.

Partnering with senior stakeholders across Finance, GTM and Product: understanding the decision they're trying to make, then building the thing that moves it

Making the value obvious: explaining in plain language what a model changed for the business, and shipping one number people trust over five nobody opens

Owning data quality, reliability and accuracy across our analytics platform, and setting the standard for how Tracksuit works with data

Running and scaling our core platform (Snowflake + dbt) and the integrations feeding it: HubSpot, Subskribe and our product database

Building self-service data products so the business can answer its own questions instead of queuing up ad hoc requests

Doing whatever the problem needs: we're a scale up, so some weeks are deep modelling and others are unblocking someone in CS, fixing a pipeline, or mentoring someone junior

You make senior people smarter, quickly: comfortable in front of execs and non-technical stakeholders, you'll push back kindly when the ask isn't the real need, and you land the "so what" without the jargon

You measure yourself on impact, not output: you can name the decisions your work changed

Low ego: you share the messy draft early, give credit generously, and care more about the right answer than being the one who had it

You love simplicity: your instinct is to delete rather than add, and you'll take the boring, well-tested model over the clever one

You thrive in the mess of a scale up: ambiguity and shifting priorities don't rattle you, and you pick up the unglamorous work without being asked

7+ years in data, with advanced SQL and dbt on Snowflake, strong modelling judgement, and the ability to own ELT pipelines and infrastructure end to end

AI tools in your daily workflow (Claude Code, Cursor, Copilot), with the judgement to verify what they produce

Nice-to-have

Experience modelling Finance or GTM data (revenue, retention, pipeline)

Prior experience in a B2B SaaS start up or scale up

Experience building or contributing to a semantic layer or metrics layer

Qualifications

Bachelor's degree (or higher) in Computer Science, Data Science, Information Technology, or a closely related analytical field — or equivalent practical experience