Wisr is committed to building a supportive, inclusive and diverse workplace, and we strongly encourage applications from all backgrounds and identities. We’re happy to accommodate any reasonable adjustments to the interview process to ensure equal opportunity for all. If you require reasonable adjustments, please reach out to us via [email protected].
Our Why, What and How
We are a proudly purpose-led ASX-listed fintech on a mission to bring people closer to financial wellness and make a real difference in the world, starting right here in Australia. By building products and experiences designed to have a positive impact on the financial health and lives of our customers, we are inching ever-closer to achieving our purpose.
We offer smarter, fairer loans that help people kick their goals sooner. Wisr App, awarded Winner of WeMoney's 2024 & 2025 'Best Mobile Experience', makes loan self-service easy and offers free financial wellness tools including credit scores, round ups, money hacks and more..
The better we do this, the more positive change and impact we can have on our customers. Now is the time to join one of Australia’s fastest growing fintechs and make an impact.
We are a people first business and value flexibility as part of our work - our team works in a hybrid working environment, typically 2 days per week in our beautiful office space.
About the job
This role sits at the intersection of product innovation, engineering and data science—supporting Wisr’s Innovation Squad in identifying, validating, and scaling new product opportunities through insights and experimentation. The Senior Analytics Engineer brings strong data infrastructure and modelling capability, coupled with hands-on experience using AI/ML, LLMs and GenAI to explore new service models and customer experiences.
As a key member of our Data team, you'll play a crucial role in supporting the development of our data models and pipelines, helping us to build a world-class data platform that serves the entire organisation.
You’ll be working with various internal stakeholders including your fellow data engineers, analysts, product owners and developers as well as cross functional teams such as Operations, Marketing and Risk teams.
What You’ll Do:
• Lead the design and build of scalable data models and pipelines that enable insight generation, experimentation and rapid iteration within the Innovation Squad
• Own and evolve the data stack supporting product development (e.g. dbt, SQL, Python, orchestration, observability)
• Build and manage data products that feed dashboards, reports and embedded analytics for product and commercial decision-making
• Ensure high standards of data quality, reliability, and performance, especially in experimental environments
• Apply LLMs, GenAI, AI/ ML to unlock new forms of customer interaction, automation, and service intelligence
• Partner with product, design and engineering leads to shape hypotheses and measure the impact of new products and features
• Develop and maintain robust documentation, schema management, and lineage tracking to ensure transparency and traceability
• Support lean market tests by instrumenting MVPs and experiments with the right telemetry and reporting infrastructure
• Contribute to innovation business cases through market sizing, revenue modelling, customer segmentation and behavioural analysis
• Stay current with emerging tools, practices and breakthroughs across AI, data platforms, and real-time analytics
About You
With strong hands-on experience using AI/ML, LLMs and GenAI, you are passionate about data, and truly enjoy the process of ingesting, transforming, integrating and managing data. You love being able to see the work you do make a significant impact in the business.
With demonstrated experience working with data systems, data pipelines and data models, you are keen to continue growing your skills in a supportive and fast-paced environment.
You’ll also have:
• 5+ years in data engineering, analytics engineering, or full-stack data roles
• Tertiary qualifications in Computer Science, Engineering, or a related technical field
• Demonstrated ability to lead projects, collaborate cross-functionally, and work independently in dynamic environments
• Strong business acumen with a commercial mindset—able to translate data into action and impact
Technical Skills
• Expert in SQL and proficient in Python for data transformation, scripting, and orchestration
• Deep experience with dbt, CI/CD for data, version control, and software engineering best practices in analytics engineering
• Strong data modelling expertise, including dimensional modelling, data mesh, data vault, and star/snowflake schemas
• Proficient in data orchestration tools such as Apache Airflow and Azure Data Factory
• Experience with major cloud data warehouse or lakehouse platform (e.g. Snowflake, Databricks, BigQuery)
• Familiarity with Docker, Kubernetes (especially AKS), and deploying data services in containerised environments
• Strong grasp of data quality, governance, and observability principles
• Proficient in building self-serve analytics using tools like Power BI, Tableau, or Looker
• Experience enabling real-time analytics and streaming data architectures
• Demonstrated experience applying AI/ML models to real-world business problems
• Hands-on with LLMs and GenAI frameworks (e.g. LangChain, OpenAI, Azure ML) for tasks such as content generation, natural language interfaces, and data augmentation
• Comfortable embedding and evaluating AI models in experimental and production environments
• Familiarity with predictive analytics or machine learning workflows
Desirable / Nice to Have
• Experience in or strong interest in the FinTech or financial services domain
• Certifications such as Azure Data Engineer Associate or dbt Analytics Engineer
• Exposure to domain-driven data architecture or data mesh implementations
• Experience with real-time data pipelines using tools like Kafka, Flink, or Azure Stream Analytics
Some of Our Perks & Benefits
• Flexible and hybrid working
• $500 every year to spend on your wellbeing
• Take an extra Annual Leave day off on us every financial year, with A Day on Wisr
• Access via WHEREFIT to discounted gym memberships, corporate discounts for wellbeing products and more!
• Generous paid parental leave to support your transition to parenthood
• Unlimited Udemy access to learn new skills
• Regular social events and awesome team offsites
• Access to our Employee Assistance Program, Uprise with up to 6 coaching sessions per year
Working at Wisr
As a purpose-led organisation on a mission to bring people closer to financial wellness, we truly believe in what we do and every person who joins our team plays a part in our success. By practising what we preach (hello, $500 wellness reimbursement, 1:1 coaching via Uprise and unlimited Udemy learning!), you are empowered to own your role, your development and the space that you play in.
We value psychological wellbeing and safety, fostering a high-performing culture which enables continuous learning and growth. Our hiring and interviewing process is designed for you to showcase your experience, skills and passion and take great pride in not just ‘ticking a box’. If this role resonates with you, we want to hear from you.
Wisr Values
• Courageously ask, “What if?”: We challenge the status quo, and we know that decisions that make us smarter, stronger, faster, more innovative always start with a “What if?”.
• ❤️ for the customer: Our internal and external customers are at the center of everything we do. We genuinely have their best interests at heart.
• Smarter parts together: We believe the real magic happens when we bring together the right mix of Smart Parts and work as a team.
• Be a stunning colleague: It’s not just about excelling in our roles, but also going the extra mile to make our colleagues and Wisr shine too.
• Growth over comfort: We love learning, and we always find opportunities to learn something new whether it is facing a fear or pushing through something uncomfortable to level up.
We are dedicated to creating an amazing candidate journey for every applicant. There's no 'shouting into the void' here. We're committed to responding to every single applicant.
