Founded in 2016, Zego is a London-based insurance technology company specializing in flexible motor insurance solutions tailored for drivers in the gig economy,
Analytics Engineer
Location
United Kingdom
Posted
2 days ago
Salary
0
Seniority
Senior
Job Description
Analytics Engineer
Zego
Title: Analytics Engineer Location: London England GB HybridBusiness IntelligenceFull time Job Description: About Zego At Zego, we understand that traditional motor insurance holds good drivers back. It's too complicated, too expensive, and it doesn't reflect how well you actually drive. Since 2016, we have been on a mission to change that by offering the lowest priced insurance for good drivers. From van drivers and gig workers to everyday car drivers, our customers are the driving force behind everything we do. We've sold tens of millions of policies and raised over $200 million in funding. And we're only just getting started. Overview of Team The Data team at Zego partners with the business to maximise the value of data. Through collaborative engineering and analytics, we ensure our teams are equipped with relevant and reliable insights to drive fast, confident and high-impact decisions. We're a small, dynamic team responsible for all aspects of data — availability, quality, integration, problem formulation, success metrics, reporting, and analytics. We take an AI-First approach: AI is now central to how we work, and we focus less on hand-writing code and more on framing problems, specifying intent, and owning the trust infrastructure (testing, contracts, observability) that the business relies on. About the Role We're looking for an Analytics Engineer who's genuinely excited about how this craft is changing. The way we build is shifting: AI tools now handle a lot of the heavy lifting of writing SQL and boilerplate, which means the job is increasingly less about typing code and more about understanding the business problem, specifying what "good" looks like, and making sure what we ship is correct and trustworthy. In practice, that means you'll design and build data models with the support of AI-assisted workflows, and you'll own a growing share of the testing, data contracts, and observability that let the rest of the business rely on our data with confidence. You'll work closely with senior engineers and stakeholders, with plenty of room to grow your technical depth and take on more ownership over time. You'll have a solid technical foundation, a natural curiosity for data, and a healthy instinct to question whether a number is actually right — not just whether a query ran. What You Will Be Doing Data Modelling & Engineering (AI-assisted): - - Work with stakeholders to understand business needs and translate them into clear, well-scoped requirements - Build and maintain robust data models and exposures in dbt, Snowflake, and Looker — using AI-assisted development to move faster, spending less time hand-writing boilerplate and more time specifying intent, reviewing, and refining - Read, debug, and critically review SQL (including AI-generated code), so we ship models we can trust - Document modelling decisions, trade-offs, and outcomes clearly - Wrangle and integrate data from multiple third-party sources (e.g. Amplitude, Segment, Google Ads) Data Quality, Trust & Operations: - - Help build and maintain the "trust infrastructure" — tests, data contracts, and observability — that lets the business depend on our models - Ensure quality, reliability, and stability across data models and pipelines - Create secure, efficient data shares for external partners (e.g. S3, SFTP, Snowflake Data Sharing) - Contribute to the continuous improvement of our data platform, tooling, and ways of working — including how we use AI in our workflows Stakeholder Enablement: - - Support business users across the company to promote a culture of data-driven decision-making - Help translate business questions into well-designed data solutions and metrics - Help enable and maintain self-service capabilities within our BI tools About You - - You'll have around 1–3 years' experience as an Analytics Engineer or in a similar role - You'll have solid SQL skills — comfortable reading, writing, debugging, and critically reviewing queries (including AI-generated ones); experience with dbt and/or Looker is a plus - You'll have some familiarity with modern data platforms (e.g. Snowflake, dbt, AWS, GCP, Looker) - You'll have experience with version control tools such as Git - You'll ideally have some exposure to Python for data or analytics engineering tasks - You'll have a meticulous eye for detail and strong problem-solving instincts — you care about whether the answer is correct, not just whether the code runs - You'll be genuinely excited about AI and how it changes our work — already using (or quickly building confidence with) AI tools to work smarter, and taking ownership of staying ahead. This is central to how our team works, not a nice-to-have. - You'll have commercial curiosity — an interest in the "why" behind the numbers and the ability to connect data work to business outcomes - Experience in the insurance sector is a plus. As more of the routine coding becomes AI-assisted, domain understanding becomes more valuable, not less — so we're keen to grow yours. What’s it Like to Work at Zego? Joining Zego is a career-defining move. People go further here, reaching their full potential to achieve extraordinary things. We’re spread throughout the UK and Europe, and united by our drive to get things done. We’re proud of our company and our culture - a friendly and inclusive space where we can lift each other up and celebrate our wins every day. Together, we’re setting the bar higher, delivering exceptional work that makes a difference. Our people are the most important part of our story, and everyone here plays a role. There’s loads of room to learn and grow, and you’ll get the freedom to steer your career wherever you want. You’ll work alongside a talented group who embrace each other’s differences and aren’t afraid of a challenge. We recognise our achievements, learn from our mistakes, and help each other to be the best we can be. Together, we’re making insurance matter How We Work We believe that teams work better when they have time to collaborate and space to get things done. We call it Zego Hybrid. While some of our team choose to come into our central London office once a week, we’re flexible - some people prefer being in once a month or even quarterly. It’s all about finding the right balance between collaborative face time and focused home-working, so we can achieve great results while maintaining a healthy work-life balance Our Approach to AI We believe in the power of AI to meaningfully improve how we work - helping us move faster, think differently, and focus on what matters most. At Zego, we encourage people to stay curious and intentional about how AI is leveraged in their work and teams to drive practical impact every day. This is your chance to do the most meaningful work of your career - and we’ll provide you with the tools, support, and freedom to do it well. Benefits We reward our people well. Join us and you’ll get a market-competitive salary, private medical insurance, company share options, generous holiday allowance, and a whole lot of wellbeing benefits. We also offer an annual flexible hybrid working contribution, which you can use to support with your travel to the office or towards your own personal development. And that’s just for starters! There’s more to Zego than just a job - Check out our blog for insights, stories, and more. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, or disability status.
Related Guides
Related Categories
Related Job Pages
More Analytics Engineer Jobs
Operations Data Visualization and Analytics Engineer IV
CareSourceFounded in 1989, CareSource is a nonprofit health care provider that aims to be a “transformative force in the industry by placing people over profits.” Bas
Role Description Develop department-wide, scalable, efficient database solutions for supporting reporting functionality. - Create ETL solutions for automated, scheduled data refreshes and regular report delivery. - Develop and deploy Power BI dashboards which provide leadership with actionable insights that drive critical business decisions. - Transform data sets and quantitative and qualitative analysis into usable and effective data for department leaders to make informed business decisions. - Build complex analytic tools that utilize the data pipeline to provide actionable insights and other key business performance metrics, historical trends or benchmarks. - Identify, design, and implement internal process improvements, automating manual processes, optimizing data delivery. - Perform complex analysis on data to provide insight and address critical business questions. - Transform data analysis and present findings in a consumable, appealing, and impactful executive level format. - Create cohesive, strategic plans for developing complex solutions when multiple stakeholders are involved. - Gather and analyze data, define and document business requirements, recommend technology requirements, review functional specs, and test relevant systems. - Develop, document and perform testing and validation as needed. - Conduct examination, testing activities, and explanation of complex data relationships to answer questions identified by the business/department. - Mentor, train, and guide junior department members on key projects. - Create, implement and enforce coding standards for the team. - Lead and participate in complex, large-effort data transformation and visualization projects which require cross functional coordination and collaboration across teams. - Solve multi-dimensional problems and create reports, dashboards and presentations. Qualifications - Bachelor’s degree in Computer Science, Management Information Systems, related field, or foreign degree equivalent. Requirements - Seven years of progressively responsible experience working with Extract, Transform, Load (ETL), Business Intelligence (BI) and database solutions to translate business requirements. - At least three of these years must be in the health plan or healthcare industry. Travel - Candidate may work remotely from anywhere in the United States. Compensation Range - $94,100.00 - $164,800.00 - CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. - In addition to base compensation, you may qualify for a bonus tied to company and individual performance. - We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package. Compensation Type - Salary Organization Level Competencies - Fostering a Collaborative Workplace Culture - Cultivate Partnerships - Develop Self and Others - Drive Execution - Influence Others - Pursue Personal Excellence - Understand the Business This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.
BI Analytics Engineer
IQVIAIQVIA is a publicly-traded healthcare intelligence company founded in 2016 upon the merger of two market leaders: Quintiles and IMS Health. With locations aroun
Role Description The Data Management team is responsible for developing, governing, and operationalizing IQVIA Digital's industry-leading healthcare and consumer data assets, which serve as the foundation for our products, analytics, business intelligence, and AI-enabled solutions. Working closely with Product and Technology teams, the organization ensures the quality, integrity, security, and scalability of data across the ecosystem. Job Overview: Designs and manages the foundational analytical data structures that enable scalable business intelligence, self-service analytics, and consistent reporting across the organization. Serves as a key partner between business and technical teams, ensuring data is modeled and governed in a way that is intuitive for consumers, aligned with business needs, and sustainable as analytical capabilities mature. Essential Functions - Designs, develops, and maintains semantic data models, including facts, dimensions, hierarchies, relationships, and business metrics that support enterprise reporting and analytics. - Partners with business intelligence developers, analysts, and stakeholders to understand analytical requirements and translate them into scalable, reusable data structures. - Defines and implements data modeling standards and best practices, including dimensional modeling, slowly changing dimensions, historical data management, and conformed dimensions. - Establishes and maintains business-friendly semantic layers that simplify access to complex healthcare and product datasets while preserving data accuracy and consistency. - Collaborates with software engineering, data platform, and business teams to ensure semantic models align with source system design, enterprise data architecture, and organizational reporting needs. - Partners with analysts and business stakeholders to operationalize approved metric definitions and business rules within scalable, reusable semantic models. - Evaluates and optimizes model performance, scalability, and usability to support both dashboard-based reporting and ad hoc self-service analysis. - Participates in data architecture discussions and provides guidance on data design decisions that impact reporting, analytics, and data consumption. - Identifies opportunities to improve data accessibility, model reusability, and overall analytical maturity across the organization. - Validates data quality and model integrity through testing, monitoring, and collaboration with engineering and analytics teams. - Supports governance efforts by establishing standards for data definitions, metric calculation, documentation, and semantic layer usage. - Serves as a technical advisor on analytics initiatives, helping teams understand the implications of data design decisions on long-term scalability and maintainability. - Identifies opportunities to extend analytical data models and curated datasets to support self-service analytics, AI-assisted data exploration, and other emerging data consumption patterns. Qualifications - Bachelor's Degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field, or equivalent experience. - 5+ years of experience in analytics engineering, business intelligence engineering, data modeling, data architecture, or a related field. - Strong experience designing and implementing dimensional data models, including fact and dimension tables, star schemas, and semantic layers. - Demonstrated understanding of data warehouse concepts and best practices, including slowly changing dimensions, historical tracking, surrogate keys, and data lineage. - Experience developing and optimizing data models that support business intelligence and self-service analytics solutions. - Proficiency in SQL and experience working with large, complex datasets. - Experience developing analytical data models within modern cloud data platforms such as Snowflake, BigQuery, Redshift, Synapse, or Databricks. - Experience optimizing analytical data structures for performance, scalability, and self-service consumption. - Experience partnering with business stakeholders to translate analytical requirements into scalable technical solutions. - Strong understanding of data governance, metric standardization, and analytical best practices. - Experience collaborating with software engineering, data engineering, and analytics teams in a cross-functional environment. - Ability to balance technical design considerations with business usability and accessibility requirements. - Strong written and verbal communication skills, with the ability to explain technical concepts to both technical and non-technical audiences. - Experience with healthcare data, product data, or other complex domain-specific datasets preferred. - Experience supporting Power BI or Tableau semantic models, tabular models, or equivalent business intelligence technologies preferred. Benefits - The potential base pay range for this role, when annualized, is $77,800.00 - $194,400.00. - The actual base pay offered may vary based on a number of factors including job-related qualifications such as knowledge, skills, education, and experience; location; and/or schedule (full or part-time). - Dependent on the position offered, incentive plans, bonuses, and/or other forms of compensation may be offered, in addition to a range of health and welfare and/or other benefits.
Analytics Engineer (SQL/BI/dbt) · Senior
DarwoftYou have just found the top firm for your next successful software development project! 🧠💻📱.
Role Description Sumamos un/a Senior Analytics Engineer para sumarse a uno de los productos más ambiciosos de una compañía argentina líder en servicios financieros digitales. Tu misión será transformar datos complejos en información accionable que permita mejorar productos, detectar oportunidades y tomar decisiones con impacto real en el negocio y en la experiencia de las personas usuarias. El rol combina analytics engineering, business intelligence, modelado de datos, experimentación y visión de producto. El impacto no se medirá únicamente por la cantidad de dashboards desarrollados, sino por la capacidad de convertir datos en iniciativas concretas, simples, personalizadas y escalables. Principales responsabilidades - Desarrollar dashboards y soluciones de visualización orientadas a la toma de decisiones. - Construir modelos de datos que permitan profundizar el análisis y responder preguntas específicas del negocio. - Transformar datos sin procesar en conclusiones relevantes, claras y accionables. - Diseñar capas semánticas orientadas al negocio que faciliten el acceso y la interpretación de la información. - Trabajar junto a equipos de Producto, Negocio, Tecnología y otras áreas para llevar adelante proyectos de analítica. - Utilizar y analizar los resultados de modelos predictivos existentes. - Impulsar Key Results mediante la identificación y propuesta de iniciativas basadas en datos y experimentación. - Construir casos de negocio junto al equipo, evaluando alternativas y respaldando las decisiones con evidencia. - Definir reglas de negocio para la extracción, transformación y modelado de grandes volúmenes de datos. - Participar activamente en las ceremonias ágiles, aportando una perspectiva analítica y orientada al producto. - Analizar resultados y proponer mejoras continuas que potencien el alcance y el impacto del producto. - Promover la autonomía de los usuarios finales mediante productos de datos simples, confiables y escalables. Qualifications - Más de 5 años de experiencia como Analytics Engineer, Data Analyst técnico, Product Data Analyst o en posiciones similares. - Experiencia trabajando con datos complejos y productos digitales. - Conocimientos intermedios o avanzados de SQL. - Experiencia intermedia o avanzada con herramientas de visualización como Amazon QuickSight, Power BI o Tableau. - Experiencia construyendo dashboards con foco en impacto, medición de resultados y autonomía de los usuarios finales. - Experiencia en modelado de datos y creación de capas semánticas orientadas al negocio. - Experiencia en extracción, transformación y modelado de grandes volúmenes de datos. - Capacidad para definir e implementar reglas de negocio sobre los datos. - Experiencia práctica con al menos una herramienta de transformación o modelado de datos, como dbt, Matillion o Google Cloud Dataflow. - Capacidad para trabajar con equipos multidisciplinarios y traducir necesidades de negocio en soluciones analíticas. - Perfil analítico, autonomía y orientación a resultados. Requirements - Conocimientos intermedios de Python o R. - Experiencia trabajando con servicios de cloud computing. - Conocimientos sobre consumo e integración de APIs. - Experiencia con librerías de visualización de datos en Python o R. - Conocimientos de experimentación con datos, incluyendo A/B testing y pruebas de inferencia estadística. - Conocimientos básicos de Data Science y modelos predictivos. - Conocimientos de estadística descriptiva e inferencial. - Familiaridad con herramientas de orquestación como Apache Airflow o Dagster. - Experiencia automatizando y programando procesos de transformación de datos. - Experiencia previa en productos financieros, banca digital o fintech. - Conocimiento de métricas financieras, comportamiento de clientes y productos digitales transaccionales. Benefits - Contratación full-time en relación de dependencia. - Pago en pesos argentinos. - Trabajo 100% remoto. - Salario competitivo. - Vacaciones y licencias correspondientes por ley. - Días personales adicionales por año. - Acceso a plataformas de aprendizaje. - Tarjeta de beneficios y descuentos. - Welcome kit. - Programas de reintegros. - Clases de inglés. - Programa de referidos. - Regalo de cumpleaños. - Healthy Break. - Celebaciones, aniversarios, fiestas de fin de año y actividades de integración al estilo Darwoft.
Analytics Engineer
OnePayThe all-in-one financial platform trusted by millions of consumers to make money better.
• Design and build production dbt models on Databricks that the organization uses as the source of truth for what’s happening in the business • Support external reporting with accurate, governed data that stakeholders and partners can trust • Own data quality: testing, CI/CD, documentation, and patterns the team follows • Build and evolve Databricks dashboards and semantic metrics for self-service across the business • Lead technically (code review, architecture, mentoring junior AEs) so the team ships faster with a higher quality bar • Partner with Data Engineering, Analytics Engineering, and analytics stakeholders to turn messy business problems into durable data products • Drive AI-native workflows: Cursor/Claude (or equivalent) in daily development; model and doc design that works for LLM consumers
