lendable - Analytics Engineer
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Requirements
• 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.
Responsibilities
• 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 STACK • You’ll work with a modern analytics stack centred around Snowflake, dbt, and Fivetran.
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