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.
- Leading triage and resolution of issues that affect the analytics pipeline or reduce trust in downstream datasets.
- Identifying opportunities to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time.
Our modern data stackYou’ll work with a modern analytics stack centred around Snowflake, dbt, and Fivetran.
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
- Strong data modelling skills and a good understanding of how analytical datasets should be structured for reliability and usability.
- Strong experience with ELT pipelines and transformation at scale, ideally using dbt.
- Experience with Snowflake or another modern cloud data warehouse.
- 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.
- A collaborative working style and clear communication across technical and non-technical stakeholders.
- Comfort using AI tools effectively to move faster, improve quality, and strengthen day-to-day analytical and engineering workflows.
- An interest in helping analysts raise their technical bar through support, mentoring, and better shared patterns.
Interview process
- Initial call
- 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.
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