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 be the analytical engine behind our business operations teams: owning the analytics layer that turns subscription, billing, customer and product usage data into clean, well modelled, trustworthy data products that drive everything from revenue reporting and forecasting to understanding how our customers succeed with our product.

You'll sit at the intersection of analytics engineering and analysis. You're equally comfortable architecting dbt models on Snowflake as you are partnering with a business lead to define a metric correctly, or crafting a dashboard that tells a compelling story. You'll work closely with teams across business operations and senior leadership, with room to expand your remit as Tracksuit scales globally.

Within the Analytics team you'll work side by side with our Senior Data Engineer, who leads the platform that moves and stores our data. Together you'll share ownership of our dbt models, with you leading what the business actually sees and uses: the business facing models, the metrics and the insights.

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

What you'll be responsible for:

Owning analytics for business operations. Partnering closely with teams like Finance and Customer Success to understand their most important questions, then delivering reliable, timely insight on revenue, ARR, churn, retention, customer health and engagement

Building and maintaining data models in dbt. Designing clean, well tested transformation logic on Snowflake that powers reporting across the business, from subscription and billing data through to customer usage patterns

Modelling business data correctly. Building dimensional and slowly changing dimension (SCD2) models so that revenue and churn metrics are point in time accurate, not just current state snapshots

Building self service data products. Trusted dashboards and well documented marts that give business teams instant, accurate access to the metrics they rely on, reducing ad hoc requests

Acting as a data quality champion. Owning accuracy, reliability and testing across your domains, and working with our Senior Data Engineer to ensure clean data flows from source systems (HubSpot, Subskribe, Vitally and our product database)

Proactively surfacing insight. Spotting trends, anomalies and opportunities before they're asked for, and presenting clear recommendations to senior stakeholders

Setting standards. Translating ambiguous business problems into well modelled, trustworthy data, establishing robust analytics engineering practices and mentoring others as our data capability grows

That's the role. Who are you?

5+ years in analytics engineering, data analytics or BI, ideally in B2B SaaS

Advanced SQL and dbt. You write clean, well tested transformation logic and understand the difference between a loose set of dbt models and a true, well layered set of marts or semantic layer

Strong dimensional modelling instincts. You know when to apply Kimball or star schemas, SCD2, or a simpler normalised approach. You model state over time correctly and care about making data trustworthy and interpretable, not just queryable

Snowflake as a primary warehouse (or equivalent cloud warehouse)

Analyst instincts. You can frame an ambiguous business question, run the analysis and tell the story, not just build the pipeline

BI tool expertise. You think about the end user when you design a dashboard

Fluency with AI tools. You use tools like Claude Code, Cursor or Copilot as part of your daily workflow, with the judgement to verify what they produce

Exceptional communication. You translate complex data into clear, actionable narratives for business leads and executives alike

A bias for proactivity. You spot questions before others do, follow through with rigour and care about the downstream business impact of your work

Nice to have:

Experience partnering directly with business operations teams such as Finance or Customer Success. You understand the metrics and data they actually need to do their jobs

Familiarity with our source systems: HubSpot, Subskribe, Vitally

Experience building or contributing to a semantic or metrics layer

BI tooling such as Sigma (or Looker, Mode or similar)

Python or R for more complex analysis or automation