Junior Analytics Engineer

Lendable

ABOUT LENDABLE Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world’s leading fintech companies and are off to a strong start: * One of the UK’s newest unicorns with a team of just over 700 people * Among the fastest-growing tech companies in the UK * Profitable since 2017 * Backed by top investors including Balderton Capital and Goldman Sachs * Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot) So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance. We get money into our customers’ hands in minutes instead of days. We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes. JOIN US IF YOU WANT TO 1. Take ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1 2. Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo 3. Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting We're looking for a Junior Analytics Engineer to join the analytical foundation for our US Cards team, the fastest-developing area of the business. In this role, you’ll work closely with analysts, product teams, backend engineers, and business stakeholders to help improve how data is structured, transformed, and consumed across the company. The role is fundamentally about contributing to a strong analytical foundation: helping teams move from question to insight quickly, while improving data quality, scalability, and maintainability. You'll be supported by experienced engineers and given the space to grow — picking up new skills, deepening your SQL and dbt knowledge, and building confidence across a modern data stack. WHAT YOU'LL BE DOING * Contributing to the data models that support credit decisions, origination, portfolio analysis, and investor reporting. * Building and improving dbt models and transformations, guided by senior engineers and in close collaboration with analysts and stakeholders. * Acting as a bridge between analysts, backend engineers, product teams, and the data platform team to help ensure data is modelled and used effectively. * Identifying opportunities to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time. * Supporting the scaling of our data infrastructure as the business grows. OUR MODERN DATA STACK You’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 solid analytics engineering fundamentals - or the drive to develop them - and the curiosity to apply them in a fast-moving environment. More specifically, we’re looking for: Essential: * Solid SQL skills and a willingness to keep improving them. * Some hands-on experience with dbt or ELT pipelines. * A collaborative working style and clear communication across technical and non-technical stakeholders. * A growing understanding of data modelling and how analytical datasets should be structured for reliability and usability. * Comfort using AI tools to move faster and improve the quality of your work. Desirable: * Experience with Snowflake or another modern cloud data warehouse. * An interest in learning from and eventually supporting analysts through shared patterns and good practices. * Fintech or scale-up experience INTERVIEW PROCESS * Initial call * Take Home Task * Technical Interview * Culture Interview 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!

Capital on Tap

We’re Capital on Tap 👋 💳 Capital on Tap started because small businesses were underserved. Big banks were slow, their products weren't fit for purpose, and small business owners often couldn't access what they needed. We set out to fix that. Today we're a financial platform - not just a credit card company. We offer a best-in-class business credit card, SME-focused spend management platform, a savings product that hit £1 billion in funds within its first year, and a growing suite of tools and financial products that make running a small business easier.  1,000+ employees, £20bn in annual card spend, 200,000+ customers, 17,000+ Trustpilot reviews averaging 4.7 stars, and we're profitable. We’ve done a pretty good job so far, but we’re just getting started!  📍 London | 🏢 Hybrid (1-2 days per week in office) Data Platform Team 🚀 Located in our growing Data Platform team, Senior Analytics Engineers play a leadership role in how data moves around the business. You will be responsible for leading the design, maintenance, and optimisation of our modern data platform, ensuring high-quality, documented data serves as a strategic asset for the entire company. What You’ll Be Doing 🗃️ * Own the global data stack including Fivetran, Snowflake, dbt, and Omni. * Create and maintain well-designed data marts through organised and tested dbt models. * Use frontier AI models (Claude, GPT) in tools like Claude Code and Cursor, plus our internal Snowflake MCP, to accelerate development, and help shape how the business adopts data and AI tooling. * Assemble large, complex data sets that meet specific business requirements. * Implement internal process improvements like Github CI/CD and automation. * Partner with stakeholders across Executive, Risk, Commercial, Finance and Engineering teams. Senior Responsibilities 👑 * Mentor and coach junior and mid-level engineers, fostering a culture of technical excellence and continuous learning. * Take full architectural ownership of the Data Platform, ensuring scalable and robust designs. * Exert strategic influence across the business to align data initiatives with long-term company goals. * Define and implement global data modelling standards and best practices across the organization. * Contribute to the long-term technical roadmap, identifying future technologies and process optimizations. Our Values & Culture 🌞 * Just Pilot: We never settle for “good enough”. We pilot new ideas fast, ask questions to figure it out, and scale quickly. * Why Not Today? Fast is as slow as we go - speed and simplicity gives us a competitive advantage. * Be a Buddy: We tap in from day one to help the team, we do the right thing even if it’s hard. * Owners and Dates: We don’t chase people. If you own a task and agree to a date, the expectation is that it gets done. * Feedback: We want our employees to flourish, so we regularly provide direct and constructive feedback. We’re Looking For 🔎 * Expert SQL skills and knowledge of data modelling (e.g., Kimball). * Hands-on experience with dbt and Git for building SQL-based pipelines. * Experience with ELT tools (Fivetran) and cloud data warehouses (Snowflake). * Familiarity developing within BI tools like Looker, Omni, Tableau, or PowerBI. * Strong analytical skills with a customer-centric approach toward Data Analysts. * Excellent interpersonal skills to translate technical concepts for stakeholders. * Proven track record of mentoring junior engineers and leading cross-functional technical initiatives. * Advanced system design and data warehousing skills, with the ability to architect complex, multi-layered data environments. Interview Process 🤝 1. First stage: 30 minute intro and values call with Talent Partner (Video call). 2. Second stage: 45 minute CV overview with Hiring Manager (Video call). 3. Final stage: Technical assessment with Team Leads and a “Meet the Team” session — 60 minutes each (Video call).   Diversity & Inclusion 🌈 We welcome, consider and encourage applications from anyone who shares our commitment to inclusivity. Join us in creating a space where authenticity thrives, and everyone can do their best work. Great Work Deserves Great Perks We try not to take ourselves too seriously (all the time) so we make sure our office is decked out with a pool table, arcade machine, beer tap, and a couple of office dogs thrown in for good measure.  Check out our benefits: 🏥 Private Healthcare including dental and opticians services through Vitality ✈️ Worldwide travel insurance through Vitality 🎁 Anniversary Rewards (£250, £500, £750, 4-week fully paid sabbatical) 👛 Salary Sacrifice Pension Scheme up to 7% match 🚘 Octopus EV Salary Sacrifice Scheme 🏖️ 28 days holiday (plus bank holidays) 📖 Annual Learning and Wellbeing Budget 👪 Enhanced Parental Leave 🚲 Cycle to Work Scheme 🚂 Season Ticket Loan 💬 6 free therapy sessions per year 🐶 Dog Friendly Offices 🍫 Free drinks and snacks in our offices       Other Info 👍Check out our ‘Top Tips’ for interviewing. ✔️Keep updated on new job opportunities by following us on Linkedin. 📧Email careers@capitalontap.com if you have any questions. Excited to work here? Apply! If you’d like to progress your career within our fast growing, profitable fintech then click apply and we will aim to get back to you within 3 working days (during busy periods this could take up to 5 working days.)

WGSN

The role We are looking to hire a Senior Analytics Engineer to join our Data Science team in London. This is a hybrid role based out of our London office. A minimum of 3 days per week in office is required. Working at WGSN Together, we create tomorrow  A career with WGSN is fast-paced, exciting and full of opportunities to grow and develop. We're a team of consumer and design trend forecasters, content creators, designers, data analysts, advisory consultants and much more, united by a common goal: to create tomorrow.  WGSN's trusted consumer and design forecasts power outstanding product design, enabling our customers to create a better future. Our services cover consumer insights, beauty, consumer tech, fashion, interiors, lifestyle, food and drink forecasting, data analytics and expert advisory. If you are an expert in your field, we want to hear from you.   Role overview  At WGSN, we believe that data is only as valuable as the decisions it empowers. As a Senior Analytics Engineer, you will sit at the vital intersection of Data Analysis and Data Engineering. Your mission is to bridge the gap between raw data and commercial value by building the internal tools, prototypes, and scalable data models that fuel our business intelligence. Unlike traditional data engineering roles focused on heavy production infrastructure, you will focus on agility—leveraging modern tech stacks and AI acceleration to spin up prototypes and methodologies quickly then scale dashboards and tools over time. As a Senior member of the team, you will be the champion of data best practices. You will initially focus on technical leadership as an individual contributor and mentoring other analysts to elevate their data modeling and software engineering skills. Over time, this role is expected to transition into direct line management responsibilities as the team expands. The team The WGSN Data team is a vibrant, multicultural mix of brilliant minds, blending global perspectives with deep expertise in retail and consumer analytics across a diverse range of industries such as fashion, beauty, interiors, and FMCG. Driven by a spirit of collaboration, we leverage our varied skill sets to transform complex datasets into high-impact insights, enabling our stakeholders to make confident, actionable, and results-driven business decisions. Key accountabilities Scalable Data Modeling: Design, build, and maintain robust, modular data models within Snowflake using dbt core, ensuring they are optimized for performance and aligned with business needs. Prototyping & Internal Tools: Rapidly build interactive GUIs, internal data applications and dashboards, and prototypes using Streamlit or similar to get actionable tools into the hands of stakeholders. Software Engineering Best Practices: Enforce modern software development standards across the analytics team, including rigorous version control (GitHub), CI/CD pipelines, and data testing paradigms. Data Integrity: Take ultimate ownership of data quality, cleaning, and transformation processes to ensure the wider business operates on a single source of truth. Team Mentorship: Actively coach and mentor data analysts, guiding them in writing production-grade SQL, adopting Python, and embracing dbt best practices. Culture of Learning: Foster an environment of continuous learning, specifically helping the team explore more advanced technologies. Translate Business to Tech: Partner with non-technical business leaders and technical engineering teams alike to translate complex commercial needs into working data solutions. Advocacy & Sharing: Proactively showcase new data products, share analytical insights with the wider business, and vocally champion data-driven decision-making in cross-functional meetings. Agile Execution: Manage your work and dependencies independently using JIRA within a sprint framework, remaining highly adaptable to changes in scope or project requirements. This list is not exhaustive and there may be other activities you are required to deliver. Skills, experience & qualifications required Data Warehousing: Advanced proficiency with Snowflake and writing highly efficient, complex SQL queries. Scripting & Modeling: Strong Python development skills for data manipulation and hands-on experience with data modeling (dbt core) UI/UX & Frontend: A proven track record of building user-friendly internal tools. A deep understanding of what makes a practical, intuitive UI/UX is what will set you apart. Experience with Streamlit is highly preferred (React is a plus). AI-Augmented Development: Comfort and experience using modern AI agents (e.g., VS Code, Cursor, Codex, or similar tools) to accelerate code generation, prototyping, and debugging. Advanced Data Tech: Exposure to or strong interest in data science concepts, machine learning workflows, vectorization/embeddings, and graph databases. Project Management: Comfortable working inside JIRA, managing sprints, and proactively calling out project dependencies. Empathetic Communicator: You are comfortable presenting to senior leadership one hour and debugging a query with a junior analyst the next. You know how to make technical concepts clear to anyone. 5-8 years of experience in Analytics Engineering or a combination of Data Analytics and Data Engineering required.  The "Follow Your Nose" Mentality: You possess an analytical mind fueled by curiosity and resourcefulness. When data looks strange or an opportunity is hidden, you have the instinct to dig deep and simplify complex information.