Senior Data & Analytics Engineer at SKUTOPIA

SKUTOPIA is a rapidly expanding Australian deep technology logistics startup dedicated to building innovative ecosystems for the e-commerce sector. Our mission is to democratize and decarbonize the logistics industry through sustainable practices and advanced technology. We offer unique solutions, including a SaaS platform for managing orders, inventory, and shipping, alongside our Robotics as a Service (RaaS) offering that utilizes in-house AI and computer vision to help merchants fulfill orders with exceptional speed and quality. As we continue to scale, we are seeking a Senior Data & Analytics Engineer to join our team and help us shape the future of logistics.

Key outcomes

• Collaborate with product and operational teams to gather requirements and deliver high-impact data projects.
• Apply software engineering principles to build and maintain efficient data pipelines, Cloud Functions, and Dataform models.
• Utilize SQL, Jinja, and Python to automate and optimize our data transformation and loading systems.
• Maintain and tune large-scale data infrastructure, including BigQuery, Datastream, and Looker.
• Design and develop robust analytic data models that provide actionable insights for our leadership and operational teams.
• Manage event-oriented datasets that feature diverse schemas and significant volume.
• Create visually compelling dashboards that effectively communicate complex data insights to stakeholders.

Requirements

• At least 5 years of professional experience in Data Warehousing.
• Minimum of 2 years of recent experience building and managing large-scale cloud data platforms, preferably within GCP.
• Advanced proficiency in SQL, data modeling, and Cloud Functions or Lambda.
• Hands-on experience with modern MPP cloud-based data warehouses such as BigQuery, Snowflake, or Redshift.
• Strong understanding of DevOps practices, including CI/CD, Docker, and Infrastructure as Code.
• Proven experience with ELT integration processes and tools like Dataform or dbt.
• Familiarity with data architecture, performance optimization, and industry best practices.
• Strong communication skills with the ability to own, track, and deliver goals both independently and within a team.
• A curious mindset and a drive to continuously learn new techniques for extracting value from data.
• Fluency in English.

Compensation

We offer a hybrid work environment to support our team members. For those based in Sydney, the role is hybrid from the start, while Melbourne-based candidates will begin remotely before transitioning to a hybrid arrangement.

How to apply

If you are ready to make an impact in a fast-paced, growing startup, we invite you to apply with your resume. Our hiring process begins with an initial screening call, followed by a meeting to discuss the role in more detail. We may then invite you to complete a skills-based task before a final interview. We encourage you to apply even if you do not meet every single requirement, as we value the unique perspective you bring to our team.