Analytics Engineer

Role & Impact

We're looking for an Analytics Engineer to turn Blinq's growing data into trusted, decision-ready insight across Product, Growth, Revenue, and Operations.

This is a high-impact role at the intersection of data engineering and analytics. You'll build the models, metrics, and self-serve foundations that help teams understand how people discover, use, and pay for Blinq. You'll work closely with stakeholders to define what matters, make data easier to use, and ensure decisions are grounded in consistent, reliable numbers. This is a hybrid role based in Melbourne or Sydney.

What You'll Do

• Own and evolve Blinq's analytics layer, building clean, reusable data models that turn raw product and business data into trusted datasets.

• Partner with Product, Growth, Revenue, Finance, and Engineering to translate ambiguous questions into clear metrics, analysis, and data products.

• Build and maintain scalable ELT workflows using SQL, dbt, and modern cloud data tools.

• Define canonical metrics and semantic models so teams work from consistent definitions across dashboards and decision-making.

• Develop high-quality dashboards and self-serve reporting that help teams move quickly without relying on one-off analysis.

• Support product analytics and experimentation, including funnel analysis, cohorts, retention, activation, monetisation, and A/B testing.

• Improve data quality and trust through testing, documentation, lineage, monitoring, and clear ownership.

• Investigate complex questions, surface the “why” behind performance, and turn insights into practical recommendations.

• Work with data and software engineers to improve instrumentation, event tracking, and the reliability of data flowing from source systems.

• Raise the bar for how Blinq uses data by improving standards, tooling, and analytics practices as the company scales.

What You'll Bring

• 3+ years in analytics engineering, data analytics, BI, or data engineering, ideally in high-growth SaaS, with a high-ownership mindset and comfort when priorities change

• Advanced SQL and dbt skills, with experience designing maintainable data models and applying strong standards for testing, documentation, and data quality

• Experience with a cloud data warehouse such as BigQuery, Snowflake, or Redshift, with a strong understanding of ELT, dimensional modelling, and data governance

• Proven ability to define trusted metrics, build useful dashboards or self-serve reporting, and partner with stakeholders to turn ambiguous questions into clear analytical work

• Strong product and commercial instincts, with the ability to connect user behaviour, experimentation, and revenue outcomes, then explain the insights in a simple, practical way