Senior Analytics Engineer — Data Platform & Self‑Serve BI

Macquarie Bank Limited; Sydney; Hybrid; AUD 180,000 - 230,000; Full time

Benefits offered by this job

Equity via Employee Share Program

Health, dental, vision insurance

Flexible working hours

Extra leave for birthdays andVolunte

Job summary

hipages is seeking a senior Analytics Engineering Lead to scale our data platform. You will mentor two analytics engineers, shape data architecture, and drive end-to-end data products using dbt, Databricks, and Tableau.

The role reports to the Head of Commercial and Data Analytics and influences a wider data community. You will lead architectural decisions, enforce data contracts, and champion reproducibility, observability, and best practices across the analytics stack.

Qualifications

• Advanced SQL with scalable data architectures
• Hands-on mastery of dbt and cloud platforms
• Experience defining data contracts and semantic layers
• Leadership experience managing analytics engineers

Responsibilities

• Lead and line-manage a team of analytics engineers
• Set analytics engineering standards and contribute to the data handbook
• Architect and implement scalable data models in dbt/Databricks
• Ensure data quality, governance, and end-to-end delivery
• Collaborate cross-functionally with Product, Engineering, Marketing and Commercial teams

Skills

Advanced SQL

dbt

Databricks

Tableau

Data Contracts

Semantic layers

Leadership

Education

Bachelor’s degree in Computer Science/Statistics/Math/Physics/Economics or related field

Tools

dbt

Databricks

Tableau

AWS/GCP/Azure

Job description

hipages is seeking a senior Analytics Engineering Lead to scale our data platform. You will mentor two analytics engineers, shape data architecture, and drive end-to-end data products using dbt, Databricks, and Tableau.

The role reports to the Head of Commercial and Data Analytics and influences a wider data community. You will lead architectural decisions, enforce data contracts, and champion reproducibility, observability, and best practices across the analytics stack.