AWS Data Engineer — Hybrid, 12-Month Contract
Summary
A 12-month fixed-term Data Engineer role in Sydney (hybrid) designing, building and maintaining scalable AWS data pipelines, ETL/ELT processes and data lake/warehouse solutions supporting analytics and reporting for a large Australian organisation. Core stack: AWS, SQL, Python, Git and CI/CD.
Sydney | Hybrid | 12 Month FTC
We're partnering with a well-established Australian organisation undertaking a major transformation of its cloud data platform. As part of a growing data and engineering team, you'll play a key role in designing, building and maintaining scalable data solutions that support analytics, reporting and business-critical decision making.
Data Engineer (AWS)
Sydney | Hybrid | 12 Month FTC
We're partnering with a well-established Australian organisation undertaking a major transformation of its cloud data platform. As part of a growing data and engineering team, you'll play a key role in designing, building and maintaining scalable data solutions that support analytics, reporting and business-critical decision making.
This is an excellent opportunity for a mid-level Data Engineer looking to work on modern AWS technologies, collaborate with experienced engineers and contribute to the evolution of a cloud-first data platform.
What You'll Be Doing
- Design, build and maintain scalable data pipelines on AWS.
- Develop and optimise ETL/ELT processes for structured and unstructured data.
- Build reliable, secure and high-performing data solutions.
- Integrate data from multiple internal and external sources.
- Support data modelling and data warehousing initiatives.
- Monitor pipeline performance and troubleshoot production issues.
- Work closely with Data Engineers, Analysts, Architects and business stakeholders.
- Contribute to best practices around automation, testing and CI/CD.
- 3-6 years' experience as a Data Engineer.
- Strong hands-on AWS experience.
- Experience building and maintaining cloud-based data pipelines.
- Strong SQL skills with experience optimising complex queries.
- Experience with Python for data engineering and automation.
- Exposure to modern ETL/ELT frameworks.
- Experience working with data lakes and/or cloud data warehouses.
- Understanding of data modelling and data quality principles.
- Experience using Git and CI/CD practices.
- Strong problem-solving skills and a collaborative mindset.
- Experience with AWS Glue.
- Experience with Amazon Redshift.
- Experience with Amazon S3.
- Exposure to Apache Spark or PySpark.
- Experience with Terraform or Infrastructure as Code.
- Knowledge of Airflow or similar orchestration tools.
- Experience working in Agile delivery teams.
- Work on large-scale cloud and data transformation initiatives.
- Modern AWS technology stack.
- Collaborative engineering culture with experienced mentors.
- Hybrid working environment.
- Long-term career growth and learning opportunities.
- Competitive salary and employee benefits.
If you're passionate about building modern cloud data platforms and want to work with AWS technologies in a collaborative environment, we'd love to hear from you.