Senior Analytics Engineer

Credit Clear Limited; Melbourne; Hybrid; AUD 150,000 - 190,000; Full time

Job summary

Credit Clear Limited is seeking a Senior Analytics Engineer to join a high-impact data team. You will build scalable data products, model data, and empower stakeholders with reliable insights across the business.

You will work with SQL, dbt and Lakehouse tech, shape data architecture, and ensure data quality, governance and observability while collaborating with Product, Engineering and Analytics to drive better decisions.

Qualifications

• A degree in Computer Science, Software Engineering, IT or a related field.
• 5+ years of relevant professional experience after completing your degree.
• Strong hands-on experience with SQL and analytical or dimensional data modelling.
• Experience building and maintaining dbt solutions, including testing, documentation and data lineage.
• A solid understanding of modern data platforms, ELT pipelines, data warehouses or Lakehouse architectures.
• A passion for solving business problems with a genuine curiosity about how organisations operate.
• The ability to engage stakeholders and translate ambiguity into clear, actionable data solutions.
• Experience applying software engineering practices such as version control, peer reviews and CI/CD to analytics development.
• Strong analytical and problem-solving skills, with a focus on data quality, accuracy and continuous improvement.
• Excellent communication skills with technical and non-technical audiences.

Responsibilities

• Build trusted, scalable data products using SQL, dbt and modern Lakehouse technologies that power reporting, product insights and business decision-making.
• Partner with Product, Engineering, Analytics and business stakeholders to understand how the business operates and translate complex problems into practical data solutions.
• Design reusable data models, metrics and business definitions that create a single source of truth across the organisation.
• Shape the future of Credit Clear's analytics platform by contributing to data architecture, modelling standards and governance practices.
• Improve trust in data through automated testing, quality controls, observability and robust engineering practices.
• Apply software engineering disciplines including Git, code reviews, CI/CD and automation to analytics development.
• Work closely with Data Engineering to optimise data pipelines, performance, reliability and scalability.
• Investigate challenging data and reporting issues, uncover root causes and drive lasting improvements.
• Enable self-service analytics by creating well-documented, discoverable and easy-to-use datasets.
• Play a key role in helping teams make faster, better decisions through high-quality data and insights.

Skills

SQL

Data modeling

dbt

Data warehouses / Lakehouse

ELT pipelines

Software engineering practices

Stakeholder engagement

Data quality

Python

Azure / Databricks

Education

Bachelors in CS / Software Engineering / IT or related

Tools

dbt

Git

CI/CD

Azure

Databricks

SQL

Job description

Senior Analytics Engineer Credit Clear | Remote, office or hybrid – your choice- Melbourne Sydney Brisbane

Love building data models people actually trust? This one's for you.

Credit Clear is an innovative ASX-listed technology company, and our data team is at the centre of how we make decisions. We're looking for a Senior Analytics Engineer to join our close-knit team of five .You'll take messy, complex data and turn it into clear, reliable insights that teams across the business use every day.

This isn't a role where your work disappears into a backlog. What you build will shape our reporting, product decisions and customer outcomes, and people across the business will see the impact.

What you'll be doing

Build trusted, scalable data products using SQL, dbt and modern Lakehouse technologies that power reporting, product insights and business decision-making.

Partner with Product, Engineering, Analytics and business stakeholders to understand how the business operates and translate complex problems into practical data solutions.

Design reusable data models, metrics and business definitions that create a single source of truth across the organisation.

Shape the future of Credit Clear's analytics platform by contributing to data architecture, modelling standards and governance practices.

Improve trust in data through automated testing, quality controls, observability and robust engineering practices.

Apply software engineering disciplines including Git, code reviews, CI/CD and automation to analytics development.

Work closely with Data Engineering to optimise data pipelines, performance, reliability and scalability.

Investigate challenging data and reporting issues, uncover root causes and drive lasting improvements.

Enable self-service analytics by creating well-documented, discoverable and easy-to-use datasets.

Play a key role in helping teams make faster, better decisions through high-quality data and insights.

What you'll bring

A degree in Computer Science, Software Engineering, IT or a related field

5+ years of relevant professional experience after completing your degree

Strong hands-on experience with SQL and analytical or dimensional data modelling.

Experience building and maintaining dbt solutions, including testing, documentation and data lineage.

A solid understanding of modern data platforms, ELT pipelines, data warehouses or Lakehouse architectures.

A passion for solving business problems, not just technical ones, with a genuine curiosity about how organisations operate.

The ability to engage stakeholders, challenge assumptions and translate ambiguity into clear, actionable data solutions.

Experience applying software engineering practices such as version control, peer reviews and CI/CD to analytics development.

Strong analytical and problem-solving skills, with a focus on data quality, accuracy and continuous improvement.

Excellent communication skills and the ability to work effectively with both technical and non-technical audiences.

A collaborative, proactive mindset and a desire to help shape the future of a growing data and analytics capability.

Bonus points (but not essential): experience with Experience with Azure, Databricks, Python or modern orchestration and BI tools.

Why you'll love working with us

Flexibility that works for you: work remotely, from the office or a mix of both

A team that has your back: join a supportive, experienced group of five data and engineering professionals

Real impact: own meaningful work that directly shapes business and customer outcomes

Set up for success: full training on our systems and ways of working

Innovation at scale: be part of a growing ASX-listed technology company