Data Platform Engineer
About the company
Across Australia's energy sector, there's growing attention on how the grid is adapting to rapid change. New renewable and storage projects are progressing at a scale that is stretching a network originally designed for a different era. Billions of dollars in projects now hinge on questions that are hard to answer quickly: where the grid is congested, whether an asset will be curtailed and what the next outage will cost.
GridScout takes the firehose of scattered market and network data and turns it into something anyone can use, whether that's a developer scoping congestion at a new site or a trader pricing the forward risk of a network outage in real time. Since our launch in September 2025, we've grown rapidly, having had the privilege of onboarding some of Australia's leading energy companies across development, operations and trading. We're grateful for the support of our customers and are now growing our team to continue building technology that helps accelerate the Australian energy landscape even further.
About the role
Working closely with our Founding Data Engineer and the team, you'll help harden, maintain and extend our data platform to meet SLAs and customer commitments, and build data features in our product. You'll get regular code review, pairing and mentoring, and take on more ownership as you grow.
What you'll do
- Help harden and optimise pipelines and infrastructure for speed, reliability, scale and cost
- Help build and maintain live, batch and event-driven pipelines on AWS for real-time and historical data from AEMO and other energy, market and network sources
- With the team, monitor pipelines, run data quality checks and resolve incidents to meet SLAs
- Build APIs, backend services and features that rely on data
- Write SQL transformations, help design data models and contribute to architecture discussions
What good looks like
First week
You've met the team, set up your environment and started exploring the product, our data pipelines and the wider platform.
First month
You've shipped your first pipeline changes with support from the team and sat in on a few customer calls to see how they use GridScout. You're getting familiar with our data sources, the basics of the NEM, and how we test, review and release.
First 3 months
You're delivering scoped pipeline and platform work with growing confidence, know your way around key parts of the data platform, and help the team keep pipelines running smoothly.
First 6 months
You've delivered pipelines and data transformations that harden the platform and power new features, have a good grasp of the domain, and are sharing ideas on how to improve the platform. You are starting to become familiar with the energy domain, and are working on other parts of the platform, which may include designing front end data heavy features for our customers.
What we're looking for
- 2 to 5 years' experience in data or backend engineering with Python and TypeScript (Node.js)
- Experience building data pipelines on cloud (e.g. AWS Lambda, S3, Step Functions, SQS, EventBridge, Glue) with help of IaC (SST or similar)
- Experience writing analytical and transactional SQL (e.g. Athena, DuckDB), and working with DynamoDB, Apache Iceberg, and graph databases
- Familiarity with Git, CI/CD and AI-native development tools (e.g. Claude Code, Cursor)
- Clear communication skills and a strong sense of ownership
Tech stack
- Data: Python and TypeScript pipelines ingesting real-time and historical data from AEMO and other energy, market and network sources. Large datasets that can be messy and deceptively hard to join.
- Storage and querying: DynamoDB, S3, Apache Iceberg, Athena, DuckDB and a graph database
- Backend: Serverless AWS (e.g. Lambda, Step Functions, SQS, EventBridge), deployed with SST
- Frontend: TypeScript and React/Next.js, with geospatial and data visualisation
You don't need to have worked with the entire stack. We care more about your data platform experience and whether you learn fast and ship well.
Nice to have
- Energy sector experience (e.g. NEM, AEMO MMS data, grid connections, trading)
- Time-series or real-time market data
- Orchestration (e.g. Airflow, Dagster), dbt, or Spark/Trino
- Early-stage startup experience
Details
- Full-time, permanent
- This is a hybrid role based in our Brisbane CBD office. We also welcome remote applications in Australia, noting preference will be given to candidates who are based in Brisbane or willing to relocate.
- Our compensation package includes salary, super and equity through our ESOP.