At Safewill, we’re transforming estate planning and end-of-life services through beautifully simple, accessible technology. Backed by investors like King River Capital, Westpac’s Reinventure Fund, Carthona Capital and Flying Fox Ventures, we’re building a digital ecosystem that makes estate planning more affordable, more personalised and more relevant for modern Australians.
Data is central to how Safewill operates. It shapes our decisions, powers our products and helps us deliver better outcomes for customers and partners.
Now we’re looking for a Data Engineer to help us expand how data is used across the organisation - from trusted self-service analytics and AI tools to embedded data products, enterprise integrations and operational workflows.
This is a high-ownership role where you’ll work alongside our Senior Data Engineer to build reliable data systems, improve engineering standards and turn an established platform into something genuinely great.
You’ll own data features from design through to production, building pipelines, models and integrations with the same rigour we expect from any production software system.
That means clean and tested code, peer reviews, structured development cycles, CI/CD, monitoring and clear ownership when something goes wrong.
You’ll work closely with Product, Engineering, Design, Legal and enterprise partners to turn complex requirements into reliable, secure and scalable data solutions.
This is also not a greenfield infrastructure build or a data science role. The core platform is already in place. Your opportunity is to improve it, extend it and raise the standard of how data is delivered and used across Safewill.
Design, build and maintain scalable data pipelines and models for analytics, AI tools and product features
Activate data through embedded products, enterprise integrations, reverse-ETL and operational workflows
Build secure outbound data integrations, including partner APIs, cloud storage and file delivery
Develop and govern integrations that connect AI agents with Safewill’s data and internal tools
Support safe and reliable natural-language access to structured data
Improve data quality, testing, observability and documentation across the systems you own
Optimise data workloads for performance, reliability and cost
Identify and address technical debt, particularly where poor abstractions create complexity downstream
Implement governance controls across access management, classification, lineage, cataloguing and data contracts
Partner with technical and non-technical teams to turn business requirements into clear technical solutions
Challenge requests where the proposed approach is not secure, feasible or appropriate
Contribute to incident response, root-cause analysis and continuous improvement
You may be a mid-level Data Engineer ready to take on broader ownership, or someone who has developed equivalent experience in a small, high-performing team.
You’re an engineer who treats data systems as production systems - not background jobs that are finished once they run successfully. You think about who uses the data, what they need from it and what could go wrong. You care about reliability, security, documentation and the long-term maintainability of what you build.
We’re likely to be a fit if you:
Bring strong platform and data infrastructure experience, with a proven track record of scoping and delivering end-to-end data pipelines, tools and models in production
Have advanced SQL skills for data transformation and querying
Have hands-on experience building pipelines and models on a cloud data warehouse, with strong Python skills and familiarity with CI/CD practices
Have worked with large volumes of data and can optimise ETL workloads for performance and cost
Bring a strong data-quality and ownership mindset - you test, monitor and treat silent pipeline failures as production bugs
Use AI confidently as both agentic coding tools and self-service analytics interfaces, enabling business users to query data through natural language
Have exposure to LLM tooling over structured data, such as text-to-SQL, RAG over tabular data or building data context for AI assistants
Can work effectively with non-technical stakeholders, including enterprise customers, Legal and Product, to turn requirements into clear technical specifications and push back when an approach is not feasible or safe
Experience with some of the following would be valuable, but you do not need to have worked with every tool or technology:
Semantic layers such as LookML, MetricFlow or Cube
Data cataloguing or metadata tools such as DataHub or Atlan
Managed ingestion tools such as Fivetran or Airbyte
Change data capture or replication tools such as Debezium or Datastream
Event, clickstream or real-time data processing using Kafka, Pub/Sub or Flink
Reverse-ETL tools such as Census or Hightouch
Data contracts, schema enforcement or data-quality frameworks
Embedded analytics tools such as Streamlit, Plotly Dash or Superset
Data masking, tokenisation or anonymisation techniques
Our Data and Engineering Culture
Data is treated as a product. We care about who uses it, how they use it and whether it helps them make better decisions or deliver better customer outcomes.
Engineering quality matters. Data pipelines and models are built, reviewed, tested and monitored with the same discipline as customer-facing software.
Ownership stays with the people who build. You’ll be involved from early scoping and technical design through to release, monitoring and iteration.
Data, product and engineering work together from the start. You’ll help shape solutions, not simply receive requirements once decisions have already been made.
We are actively exploring how AI changes the way people access and use data. You’ll have space to experiment, form a view and help establish practical standards as the technology evolves.
We handle sensitive personal, financial and estate information. Privacy, security and responsible data use are part of every decision, not a final compliance check.
We live by our SAFE values:
Speed: We move quickly with purpose
All-in: We win as a team
Find the Impact: We focus on what matters
Elevate: We raise the bar, every day
TL;DR We’re rewriting how Australians deal with death by making estate planning simple, accessible and modern through great technology. At Safewill, you’ll take real ownership of production data systems, work close to the problems that matter and help shape how data and AI are used across a growing business.
