Data Engineer

About the Role

Are you passionate about translating complex data into meaningful business outcomes?

We are looking for two motivated and detail-oriented Data Engineers to play a key role in delivering large-scale data transformation initiatives across the organisation.

In this role, you will design, build, and optimise our data ecosystem—supporting the migration of data from legacy systems into modern cloud platforms. You will be responsible for designing, developing, and optimising scalable data pipelines that transform raw data into high-quality, reliable datasets for business use.

You will take ownership of data pipelines, data models, and transformation frameworks, ensuring they are scalable, secure, and aligned with enterprise data standards.

If you enjoy solving complex data challenges, improving systems, and enabling high-quality, governed data migrations, this is your opportunity to make a real impact.

We have a full-time permanent opening available, with opportunities to be based in Brisbane (Australia), Christchurch (NZ), or Selangor (Malaysia).

In this role, you will:

• Analyse data and provide actionable insights to support business decisions
• Design, build, and optimise scalable data pipelines and transformation processes
• Develop and standardise data architecture and migration frameworks
• Ensure data quality, reconciliation, and accuracy across systems
• Collaborate with business and technical stakeholders to ensure clear communication and alignment
• Uphold strong accountability, teamwork, and sound judgment in delivery

Who We Are

Sime is a partner of choice for some of the world’s best brands in the Industrial and Motors sectors. With operations in 17 countries and territories and a strong footprint in Asia Pacific, we continue to grow, delivering sustainable value to our stakeholders through operational excellence, high-performance standards and good corporate governance.

Why Sime?

You’ll have access to:

• Opportunities for training, mentorship, and career development specific to your role.
• Competitive remuneration package and annual salary reviews.
• Access to growth opportunities at a regional, national, and international level through our global Sime network.
• Dedicated programs and utilities to support your physical, mental, and financial health, such as our Employee Assistance Program, free health checks, and discounted private health insurance.
• Employee discounts, rewards, and incentive programs.
• Paid parental leave options.
• Salary continuance insurance.

About You

A successful teammate will have:

• Bachelors degree in relevant discipline
• Hands-on experience with modern transformation tools such as dbt, Informatica, or similar enterprise platforms
• Experience working with cloud-native data platforms such as Snowflake, Azure Synapse and ideally Fabric
• Strong understanding of cross-system data lineage and end-to-end impact analysis, essential for complex migration
• Proven experience working on large scale migration projects performing data profiling, data mappings, and data cleansing and standardisation.
• Ability to design and build scalable data pipelines for ingestion and transformation in cloud environments
• Experience supporting data migration activities like testing, reconciliation and cutover
• Strong collaboration skills with proven ability to work with business stakeholders, data owners, and governance teams to validate mappings and ensure alignment
• Ability to gather, analyse and document technical and business requirements.
• Experience with ERP migrations (e.g., AX 2012 to D365) is highly desirable.

To Apply: Hit the ‘Apply Now’ button

Enquiries: Please call 1300 071 618

Contact Person: Brianna Smith – Brianna.l.smith@hastingsdeering.com.au



Hastings Deering / Sime follows a Pre-Employment Process for all successful applicants, which includes two employment references, a National Police Check and a medical assessment. These checks are essential to your application, and your Talent Acquisition Partner will support you through the process.