Airtasker, the tech company that connects people who need to get things done with those who have the skills to do it, is looking for an Analytics Engineer to join our growing Data Platform team. In this role, you will be at the heart of our data ecosystem, helping to build, maintain, and scale the infrastructure that empowers our entire organisation.
Your mission will be to develop the robust infrastructure, tooling, and data models that enable data analysts, data scientists, and machine learning engineers to work efficiently and effectively. You will be instrumental in shaping a reliable and scalable data foundation, making a significant impact on how data is used across the company.
This is an ideal position for someone with foundational data skills who is eager to grow their experience in cloud infrastructure, MLOps, and modern data and analytics engineering practices.
Build & Maintain Data Pipelines: Design, develop, and maintain clean, performant, and reliable data models and transformation pipelines using dbt and SQL.
Develop Data Infrastructure: Contribute to the design, deployment, and management of our cloud data infrastructure on AWS using tools like Terraform.
Enable Self-Service Analytics: Build and support tooling and foundational datasets that empower stakeholders to answer their own questions and gain insights independently.
Champion Best Practices: Promote and apply software engineering best practices to our data domain, including version control (Git), CI/CD, testing, and documentation.
Collaborate & Educate: Work closely with data analysts, scientists, and other engineers to understand their needs, provide support, and share your knowledge of our data platform.
Support MLOps Initiatives: Assist in building out our MLOps capabilities, including supporting the deployment and operationalisation of models in AWS SageMaker.
Automate & Innovate: Use Python to develop tooling and automate processes to improve the efficiency and reliability of our data platform.
A foundational understanding of the data lifecycle, from ingestion to analysis.
Proficiency in SQL for data modeling, transformation, and analysis.
Hands-on experience with dbt in a professional or personal project setting.
Familiarity with software engineering principles like version control, testing, and CI/CD.
A keen interest in learning about cloud platforms (we use AWS) and Infrastructure as Code (Terraform).
Some experience with Python for scripting or data manipulation is a big plus.
Excellent problem-solving skills and the ability to work through ambiguity.
A collaborative spirit, a growth mindset, and a genuine passion for data.
Experience with a modern cloud data warehouse like Snowflake.
Exposure to AWS data services (e.g., S3, Glue, Lambda).
Familiarity with MLOps concepts or tools like SageMaker.
Our people team at Airtasker are dedicated to designing an industry leading people experience. This means creating an environment where you are empowered to do your best work and realise the full potential of your skills.
Rewarding
Belonging
Growing
Celebrating
At Airtasker we believe in culture add - that each person is different and has their own background, learnings and unique experiences that can add to the Airtasker cultural tapestry. We pride ourselves on our inclusive culture, and encourage applications from people of all backgrounds.