Engineering Lead - Data

Lendi Group is a market-leading digital platform business that is focused on revolutionising the entire property journey. It operates Lendi - Australia’s original and #1 digital mortgage brand - and the iconic Aussie franchise.

Powered by an advanced AI proprietary platform, a national network of 1,300 brokers, 230 retail stores, a team of experienced buyer’s agents, integrated property search and conveyancing, Aussie is supporting customers at every step of their property journey to find, buy and own with more confidence than ever before. Lendi Group’s loan book is more than $100b and it was named Australia’s Aggregator of the Year for 2024.

To learn more about life at Lendi Group check out our blog: https://www.lendi.com.au/inspire/category/life-at-lendi/

Why Join Us?

• Innovation at Our Core – We challenge the status quo and push boundaries to create better solutions.
• Work with the Best – Collaborate with some of the brightest minds in fintech, financial services, and strategy.
• Make an Impact – Contribute to meaningful projects that shape our business and the future of property finance.
• Grow & Evolve – Develop your skills and advance your career in a fast-moving, purpose-driven environment.

About the role

Lendi Group is at the forefront of innovation in the mortgage and finance industry. We are committed to leveraging data to drive business decisions, optimise operations, and deliver exceptional value to our customers and brokers. As we continue to grow, we are expanding our data engineering and insights capabilities. 

We are seeking a highly skilled and motivated Data Engineering Lead to join our team in Sydney to be accountability for the strategic elements of the Lendi Group Data Platform.

The ideal candidate will be a strong leader of technical teams, with a strong understanding of data architecture, data modelling, analytics engineering, data engineering and experienced with the management of cloud native modern data platforms. You will be responsible for managing a modern data stack and modern data engineering development practices. 

Collaboration

• Work within a cross-functional agile team to design, build, and deliver high-quality data solutions that support business and product outcomes.

• Partner with data analysts, data scientists, product, and engineering teams to translate business requirements into scalable technical solutions.

• Collaborate with platform, infrastructure, and AI teams to ensure the data platform supports the group’s AI-native strategy.

Team Leadership

• Lead and mentor a team of around five data and analytics engineers, ensuring strong delivery standards, code quality, and best practice adoption.

• Drive a culture of ownership, accountability, and continuous improvement within the data engineering function.

• Provide hands-on guidance and technical leadership while maintaining high delivery velocity.

Data Engineering Delivery

• Own end-to-end data pipeline development and maintenance using the modern data stack (Python, dbt, Airflow, Snowflake, Databricks, AWS).

• Lead development, testing, and deployment for cloud data warehouse and lakehouse environments.

• Design and implement logical and physical data models that ensure performance, scalability, and maintainability.

• Oversee Power BI semantic models, ensuring governance, consistency, and reusability across business reporting layers.

• Implement CI/CD automation and infrastructure-as-code practices (Terraform, Buildkite or equivalent).

Platform Ownership & Optimisation

• Manage the data platform budget, including vendor management, cost optimisation, and resource utilisation.

• Drive platform reliability, scalability, and performance improvements.

• Ensure data platform security through robust access management, collaboration with Cyber and Platform teams, and secure-by-design practices.

• Oversee provisioning of AI and BI services across the platform, supporting the company’s AI transformation goals.

Data Governance & Quality

• Ensure compliance with data governance, privacy, and security frameworks.

• Monitor and resolve data quality issues, ensuring completeness, accuracy, and integrity across data products.

• Champion documentation, lineage tracking, and transparency across all data assets.

Issue Management & Documentation

• Maintain detailed documentation for data pipelines, models, and solutions.

• Support issue and incident management, driving root-cause analysis and preventive improvements.

• Contribute to internal design standards, training material, and onboarding resources.

• 8+ years’ experience in data engineering, with a proven track record delivering modern, scalable data platforms in cloud environments.

• Hands-on leader with experience managing and mentoring a team of 3–5+ data engineers, setting engineering standards and driving delivery excellence.

• Deep technical expertise in SQL and modern cloud data warehouses (Snowflake, Databricks, AWS RDS), including end-to-end ETL/ELT pipeline development.

• Proficient in Python and familiar with dbt, Airflow, or similar orchestration and transformation tools.

• Strong understanding of data modelling, dimensional design, and data warehousing principles.

• Knowledge of data governance, observability, and data quality frameworks, with practical experience embedding these into engineering workflows.

• Demonstrated ability to work in fast-paced, product-led environments, balancing hands-on delivery with strategic platform thinking.

• Excellent communication, stakeholder management, and cross-functional collaboration skills — able to influence engineers, product teams, and senior leaders.

• Strong problem-solving and ownership mindset, with a bias for action and continuous improvement.

Success in this Role Looks Like

• Stable and reliable data platform: Pipelines and workflows are automated, monitored, and performing reliably; incident rates are reduced.

• Engineering uplift: Team operates with clear standards, CI/CD discipline, and strong code ownership.

• Modern stack adoption: dbt, Airflow, Snowflake, and Databricks are embedded into engineering workflows with proper testing and observability.

• Governance in practice: Data quality, lineage, and access controls embedded in day-to-day delivery.

• Cross-functional trust: Data engineering team is recognised as a trusted partner to product, analytics, and AI teams.

• Optimised platform spend: Cost governance models in place and driving measurable savings.

• AI enablement: Platform is ready to support Lendi Group’s AI-native roadmap through reliable data and automation foundations.

• Enjoy the flexibility of remote working arrangements. We offer a highly flexible hybrid structure to suit your individual needs
• We offer extended Paid Parental Leave: we celebrate our growing Lendi Group family with up to 26 weeks leave for primary carers and up to 4 weeks for secondary carers.
• An additional week’s Loyalty Leave each year after reaching 3 years’ service.

We are a people-first company that invests in initiatives to promote a healthy work environment, such as offering an Employee Assistance Program and social groups such as our industry-leading Women in Technology group.

Our culture is guided by our 3 core values: We Are Stronger United; Act Like You Own It; and Keep Home Loans Human. Our values are part of our core DNA that helps Lendi Group to attract, engage and evolve the right talent and build best-in-class products.

Lendi Group is a 2024 Circle Back Initiative Employer; we value a positive candidate experience and commit to respond to every applicant. Once we have received your application, we will reach out to you via email.

Feeling like you don’t meet all the skills listed? That’s ok; we are always on the lookout for different skills, experience, and qualities and so we’d still like to hear from you.

#Lendigroup #LI-GR2 #LI-Hybrid