Data Engineer

• 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.

• Design, build, and maintain scalable data pipelines using modern data stack tools (dbt, Airflow, Python).
• Take ownership of troubleshooting and resolving issues in data workflows, ensuring reliable and timely data delivery.
• Work with Databricks and Snowflake environments to support ingestion, transformation, and modelling of data.
• Contribute to development and optimisation of Unity Catalog, Delta Live Tables, and Spark within Databricks.

• Collaborate with senior engineers and analysts to design and implement data models that support analytics and product needs.
• Translate business requirements into technical solutions, including prototyping and proof-of-concepts.
• Apply best practices in data modelling (Kimball, Data Vault, etc.) to ensure scalable and performant solutions.

• Partner with data analysts, engineers, and business stakeholders to clarify requirements and deliver solutions.
• Clearly communicate progress, challenges, and technical considerations to both technical and non-technical stakeholders.

• Maintain up-to-date documentation for pipelines, workflows, and solutions, ensuring knowledge is shared across the team.
• Support data governance initiatives by monitoring data quality, applying standards, and flagging anomalies.

• Proactively identify opportunities to optimise pipelines and improve performance in Databricks and Snowflake.
• Support ongoing platform improvements and contribute to scaling best practices across environments.

• Stay across emerging trends and best practices in cloud data engineering.
• Mentor junior engineers where appropriate and contribute to team knowledge-sharing activities.
• Actively participate in improving team culture, ways of working, and engineering standards.

• 2–4 years’ experience in data engineering or a related role.
• Strong SQL skills and experience with data modelling techniques (e.g., Kimball, Data Vault).
• Hands-on experience building and maintaining data pipelines using dbt, Airflow, or similar orchestration/ETL tools.
• Practical exposure to Databricks (Spark, Delta Live Tables, Unity Catalog) and Snowflake (warehousing, performance tuning, security).
• Proficiency in Python for data processing and automation.
• Understanding of data governance, data quality, and best practices for managing cloud data platforms.
• Strong problem-solving skills with the ability to troubleshoot and resolve data pipeline issues.
• Good communication skills to collaborate with engineers, analysts, and business stakeholders.

• Experience working in cloud platforms (AWS, Azure, or GCP).
• Familiarity with CI/CD, infrastructure-as-code (Terraform, Git, etc.).
• Exposure to BI/visualisation tools (Tableau, Power BI, or similar).
• Previous experience in a mid-size to large data environment, supporting cross-functional teams.
• Interest in mentoring juniors and contributing to team knowledge-sharing.

• A vibrant, relaxed, yet professional culture.
• Hybrid working arrangement designed to support work-life balance, while fostering meaningful connection and collaboration.
• A holistic wellbeing programs offering 24/7 support, including medical, mental health, and financial wellbeing services to enable our workforce to thrive at home and work.
• Generous paid Parental Leave: we celebrate our growing Lendi Group family with 18-26 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.
• Wellness initiatives with a strong focus on psychological safety.

Lendi Group