Data Engineer

About the role:

We're looking for a hands-on Data Engineer to join us on a 12-month max-term contract and play a key role in supporting and scaling our growing data infrastructure.

In this role, you'll be responsible for building and maintaining scalable ETL/ELT pipelines using Databricks and modern cloud tools. You'll also step in to temporarily support our business intelligence needs, developing and maintaining reports and dashboards in ThoughtSpot (or a similar BI platform).

You'll collaborate closely with our Lead Data Engineer, who will provide architectural guidance and help drive the strategic direction of our data transformation initiatives.

This role is a great fit for a data engineer who enjoys working across the full data stack—from raw data ingestion and transformation all the way to the BI layer—with a strong focus on data quality, reliability, and usability.

We offer a hybrid work arrangement for Sydney-based candidates: 1 days in the office and 4 days remote each week, giving you the flexibility to do your best work. Remote applicants are welcome to apply.

Key Responsibilities:

Data Engineering

• Build, maintain, and optimize robust ETL/ELT pipelines using Databricks.
• Contribute to the design and implementation of data lake and data warehouse architecture.
• Translate business requirements into reliable and scalable data solutions.
• Collaborate with the Lead Data Engineer on data modeling, pipeline design, and cloud infrastructure best practices.
• Implement monitoring, alerting, and logging for data pipelines to ensure data integrity and reliability.
• Participate in sprint planning, technical documentation, code reviews, and team collaboration rituals.

BI & Reporting Support

• Maintain and support dashboards and reports in ThoughtSpot.
• Assist stakeholders with ad hoc data queries and visualization needs.
• Ensure availability and accuracy of key business metrics during the analyst's leave period.
• Translate complex datasets into usable, decision-support insights.

Key Requirements:

Essential

• Strong experience building and managing ETL/ELT pipelines in Databricks or similar platforms.

• Proficiency in Python and SQL for data processing, transformation, and analysis.

• Deep knowledge of data modeling and warehousing concepts.

• Experience with BI tools, preferably ThoughtSpot (or Power BI, Tableau, Looker).

• Solid version control and collaboration practices (e.g., Git).

• Ability to collaborate closely with both technical and non-technical team members.

• Effective communication and problem-solving skills.

Desirable

• Exposure to DevOps practices such as CI/CD (e.g., Azure DevOps), infrastructure as code (e.g., Terraform).

• Experience working in a remote or distributed team environment.

• Experience working with cloud environments (AWS, Azure, or GCP).

• Familiarity with AWS services like S3, Lambda, EC2, SQS, and SNS.

Personal Attributes

• Curious, proactive, and eager to learn.

• Comfortable balancing engineering depth with occasional BI support.

• Strong ownership mindset and attention to detail.

• Organized and efficient; able to manage priorities across domains.

If you would like to be a part of the Wilbur team then please submit your application. We look forward to hearing from you