Original listing text, shown exactly as published by the company.
What you'll be doing
- Owning and improving the data models that support lending decisions, pricing, portfolio analysis, and investor reporting.
- Driving the development of our dbt models and transformation layer, working with analysts and stakeholders to improve the speed and quality of insight generation.
- Helping define good modelling patterns, architecture, and implementation standards across the analytics engineering layer.
- Supporting and mentoring analysts at different technical levels, helping them build stronger engineering habits and become more effective with data.
- Acting as a bridge between analysts, backend engineers, product teams, and the data platform team to make sure data is generated, modelled, and used effectively.
- Identifying opportunities to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time.
- Scaling our data infrastructure to proactively support the requirements of a rapidly growing business.
Our modern data stackYou’ll work with a modern analytics stack centred around SQL, Snowflake, dbt, Fivetran and Claude.
What we're looking for
We’re looking for someone with strong analytics engineering fundamentals and the ability to apply them pragmatically in a fast-moving environment.
More specifically, we’re looking for
Essential
- Strong SQL skills
- Strong experience with ELT pipelines and transformation at scale, using dbt.
- Excellent stakeholder management skills, with a proven ability to influence and negotiate with both technical and non-technical stakeholders
- Strong data modelling skills and a good understanding of how analytical datasets should be structured for reliability and usability.
- Good judgement in balancing longer-term platform improvements with day-to-day business needs.
- The ability to spot inefficiencies in existing data workflows and improve them independently.
- Comfort using AI tools effectively to move faster, improve quality, and strengthen day-to-day analytical and engineering workflows.
Desirable
- Experience with Snowflake or another modern cloud data warehouse.
- An interest in helping analysts raise their technical bar through support, mentoring, and better shared patterns.
- Fintech or scale-up experience
Interview process
- Initial call with an engineer
- 15 minute Cognitive Assessment
- Onsite or Video Interview lasting 90 minutes, comprising of:
- Introduction of the team and kind of work you could be doing daily
- Interactive architecture/design exercise
- Questions you may have about the company, role, etc.
- A 60 minute chat with this role's primary stakeholders
- Cultural/behavioural questions
- Product mindset and ability to collaborate and communicate
Life at Lendable
- Winning team: the opportunity to scale up one of the world’s most successful fintech companies
- Flexible working: flexible approach tailored to each role. Hybrid roles require three days in-office weekly; fully remote roles include regular opportunities for in-person connection through socials and off-sites
- Socials & connection: opportunities and events to come together, socialise, and get to know each other beyond the office walls
- Health coverage: support for your physical and mental wellbeing, including private health cover
- Retirement & savings: long-term financial wellbeing through retirement savings plans
- Employee referral programme: earn a competitive bonus when you refer successful new team members
- Office meals & snacks: enjoy a fully stocked kitchen, plus complimentary lunches prepared by in-house chefs on in-office days at select locations
- Sustainable commuting: cycle-to-work and electric vehicle salary sacrifice schemes available in select locations
Please note: The availability and details of specific benefits vary by location and role. For more information, please speak to your Talent Partner.
Check out our blog!
