WHO IS PLENTI?

Plenti is a fintech lender, providing faster, fairer loans by leveraging its smart technology. Plenti is a dynamic and innovative business that is growing strongly. By continuing to deliver better customer experiences, Plenti is taking market share from incumbent players in the personal lending, renewable energy, and automotive finance markets.
We are a fast moving and ambitious business that seeks to recruit smart and capable people, who can take ownership of their role to help the business thrive. With over 250 people based in Australia, Plenti is of a size where everyone can make a difference in their role and help us realise our very big ambitions as a team, as we go about building Australia’s best lender.
Plenti is a founder led business that launched in 2014, listed on the ASX since 2020 with annual revenue of over $250 million and a loan portfolio of over $2.5 billion.

ABOUT THE ROLE:

As the Engineering Manager - Data Analytics, you will serve as both a technical leader and a collaborative team leader at the heart of our data engineering and analytics function. You’ll oversee the design, development, and optimisation of our Databricks-based data pipelines and models, ensuring seamless support for analytics, reporting, and AI use cases across our business. This is a hands-on leadership role, responsible for mentorship, team coordination, and championing best practices.

WHAT YOU’LL BE DOING:

• Architecting and building data solutions on Databricks to power our core reporting, analytics, MLOps, and generative AI initiatives
• Designing, building, and operating scalable and reliable data integration pipelines with a cloud-native approach
• Overseeing and coordinating the data engineering and analytics team’s efforts to ensure the timely and efficient delivery of high-impact analytics solutions
• Serving as a key collaborator with analysts, data scientists, and business stakeholders to translate requirements and maximize business value from data
• Contributing to strategic planning and the team’s roadmap, aligning initiatives with organizational priorities
• Mentoring team members and fostering a supportive, collaborative environment
• Establishing, maintaining, and promoting data standards, governance, and best practices
• Proactively identifying opportunities to improve data architecture, tooling, and automation across the data platform