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.
As our Senior Analytics Engineer, you'll specifically be responsible for:
- 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
That's the role - who are you?
- 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
We put a real focus on fair compensation for our people and their roles
We run comprehensive full-cycle comp reviews annually, as well as rolling promotions when you've levelled up. Your salary is supplemented with our best-in-class benefits package, as well as generous ESOP.
Why join us at Tracksuit?
Tracksuit is one of Australasia's fastest-growing startups - and at just under 5 years old, we're already partnering with 1,000+ amazing brands across NZ, AU the US and UK including MyFitnessPal, Steve Madden, Bondi Sands, Athletic Brewing and many more.
We're building the common language for brand - and we're doing it with a globally distributed, tight-knit, and ambitious team. We're all about transparency, trust, learning, and building something we're proud of.
FYI - We're pet-friendly in principle and practice - with the occasional four-legged visitor adding to the charm, not the chaos.
Here's a few things we think make Tracksuit a great place to work:
Compensation: Competitive market-rate salaries. We've also got a fully transparent compensation framework, so everything's out in the open.
Equity: Every Trackstar gets a slice of the pie through our ESOP program.
Wellbeing perks: 6 weeks paid leave, an annual wellness bonus, and access to top tier EAP services.
Parental support: 12 weeks paid parental leave for all parents, extra support for IVF, and a phased return to work.
L&D budget: $1000 per year to spend on your own learning and development - plus heaps of internal opportunities for growth.
Flex where it counts: We're office-first, with stunning hubs in Auckland, NYC, London, and Sydney - and we support flexibility in how you manage your time.
But don't take our word for it! You'll be joining the:
- Mumbrella Marketing Company of the Year 2022
- HRD Employer of Choice <200 Staff 2024
- NZ Hi Tech Awards, Emerging Company of the Year 2024
- AFR Best Place to Work Media and Marketing (4th place) 2024
This is a high-impact role at the intersection of data quality, analytics engineering, and cross-functional enablement - ideal for a senior analytics engineer who wants real ownership of the analytics infrastructure that keeps a fast-growing global company running. Come be part of a team known for high standards, technical rigour, and genuinely caring about the downstream impact of the data we build.
