Data Engineer

Join an innovative Australian technology company building scalable cloud-based platforms and data solutions for mission-critical applications.

This is a hands-on engineering role where you'll work with large-scale telemetry and time-series data, helping build the data platform that powers real-time monitoring, engineering insights, and operational decision making. Working closely with Cloud and Software Engineering teams, you'll design and build scalable data pipelines, develop real-time dashboards, and deliver reliable data infrastructure.

You'll have the opportunity to work with modern cloud technologies and solve complex data engineering challenges.

The Role

You will:

• Design, build and maintain scalable data pipelines for high-volume telemetry and time-series data.
• Develop ETL/ELT processes to transform raw operational data into clean, analytics-ready datasets.
• Build and maintain Grafana dashboards for real-time monitoring and operational visibility.
• Develop cloud-based data workflows using AWS services including Kinesis, Glue, S3, Athena, Lambda and DynamoDB.
• Manage and optimise time-series databases such as InfluxDB, Amazon Timestream or similar platforms.
• Work closely with Cloud and Software Engineers to ensure data systems are scalable, secure and cost efficient.
• Implement monitoring, alerting and data quality controls to ensure reliable pipeline performance.
• Contribute to Infrastructure as Code using AWS CloudFormation.
• Support engineering, product and operations teams by delivering reliable datasets, APIs and documentation.
• Continuously improve data pipeline performance, observability and operational efficiency.

What You Bring

You'll have:

• 3+ years' experience in Data Engineering or a similar role.
• Strong Python development experience for data processing and pipeline automation.
• Experience with AWS data services including Kinesis, Glue, S3, Athena and Lambda.
• Experience building Grafana dashboards and visualisations.
• Knowledge of time-series databases such as InfluxDB, Amazon Timestream or similar.
• Strong SQL skills and experience with data modelling.
• Experience developing ETL/ELT pipelines and using orchestration tools such as AWS Step Functions, Apache Airflow or similar.
• Understanding of data quality, testing, monitoring and observability practices.
• Experience using Git and CI/CD pipelines such as GitHub Actions.
• Strong analytical, troubleshooting and communication skills.
• A proactive approach and willingness to learn new technologies.
• Experience working with IoT, connected devices, industrial systems, or large-scale telemetry data is highly regarded.
• Experience with streaming data architectures such as Kafka or Amazon Kinesis is beneficial.
• Familiarity with Infrastructure as Code using CloudFormation, along with knowledge of AWS security best practices and IAM, is desirable.

Why This Role

You'll help build cloud-native data platforms that support large-scale, real-world applications. Working alongside experienced Cloud, Software and Platform Engineering teams, you'll have the opportunity to solve complex engineering challenges using modern AWS technologies, streaming data architectures, and scalable data pipelines.

Reality Check

This role requires hands-on engineering expertise, a willingness to learn new technologies, and the ability to collaborate closely with cross-functional teams. You'll need to be proactive and have strong analytical, troubleshooting, and communication skills to succeed.

Interested?

If you're passionate about cloud-native data engineering, real-time data processing, IoT platforms, and building scalable data solutions, we'd love to hear from you.

Apply now or get in touch for a confidential discussion about the opportunity.

Simon Melano
0485 991 211
simon@runtimerec.com