• Own the design, implementation, and evolution of certified data models, semantic layers, and trusted business metrics that become the foundation for reporting and decision-making across TechnologyAdvice. • Partner directly with Finance, Revenue, Marketing, Editorial, Product, and Engineering stakeholders to understand business questions, define trusted metric definitions, and translate ambiguity into scalable data solutions. • Design, build, and maintain analytics models, transformations, and data products using modern analytics engineering practices. • Establish and continuously improve data quality through automated testing, validation, monitoring, and observability to ensure business stakeholders can trust the data they use every day. • Improve the architecture, organization, and maintainability of our analytics platform, continuously identifying opportunities to simplify, standardize, and modernize our Business Intelligence ecosystem. • Collaborate with DevOps and Software Engineers to improve data ingestion, lineage, orchestration, governance, and platform reliability across the analytics stack. • Apply AI-assisted development practices to accelerate SQL development, documentation, testing, root cause analysis, and engineering productivity while maintaining rigorous standards for data quality and accuracy. • Document business definitions, data models, metric logic, and architectural decisions to improve transparency, onboarding, and long-term maintainability. • Continuously evaluate new technologies, AI capabilities, and analytics engineering practices that improve data quality, governance, developer productivity, and stakeholder confidence. • Own trusted data products end-to-end—from business discovery and metric definition through implementation, validation, adoption, and continuous improvement. • Champion a culture of trusted data by helping teams adopt certified data models and reducing duplicate business logic across reports, dashboards, and applications.

Role Description As an Intern in the Analytics & Insights Engineering team, you will primarily work on internal technical projects that strengthen Astrafy’s data stack and ways of working. Under the guidance of consultants and your entity manager, you will contribute to both the business and technical sides of these use cases, while investing heavily in learning and developing your skills. Depending on your progress and project needs, you may also have the opportunity to contribute to selected customer engagements under the supervision of experienced consultants. You will also have the opportunity to use the latest AI technologies to support your day-to-day work on internal technical topics and accelerate how you learn, build, and deliver. On the business side: - Collaborate with internal stakeholders (consultants, Team Leads, product owners) to understand internal needs and priorities for our data and analytics stack. - Help refine and clarify requirements for internal tools, dashboards, and processes to ensure they align with Astrafy’s business objectives. - Assist in analyzing internal datasets (for example operational, financial, or product-related data) to identify opportunities for better reporting and decision-making. - Support internal workshops or working sessions to define and validate key metrics (KPIs) used across teams. - Contribute to the definition of visualizations and internal dashboards that make data easy to understand and use. - Depending on your progress and the projects in flight, you may also be involved in specific, well-scoped client-related tasks, mainly as support to a consultant. On the technical side: - Contribute to building and improving internal data models in BigQuery and dbt that support Astrafy’s own reporting and analytics needs. - Help develop and maintain LookML models and internal dashboards used by the Astrafy team. - Implement and test simple business rules and data transformations to ensure internal data is consistent, reliable, and well documented. - Support the creation of internal reports and monitoring dashboards with a strong focus on usability and clear data presentation. - Explore and, where relevant, leverage AI-driven solutions to improve internal workflows and user experience. - Depending on your progress and the projects in flight, you may also be involved in specific, well-scoped tasks on client projects, always under the guidance of a senior consultant. In addition to these responsibilities, we strongly value knowledge-sharing and community engagement. At Astrafy, we are active contributors on platforms like Medium, where we regularly publish articles to share our expertise, insights, and innovations. As part of the role, you will be encouraged to contribute to articles and internal documentation, sharing what you learn and helping to grow Astrafy’s impact and knowledge base. Learn fast, deliver small but reliable pieces of work, and progressively gain autonomy with the support of the team. Your success is measured by your ability to learn, collaborate, and ship incremental value with quality and consistency. Qualifications - Basic experience with enterprise-grade BI or analytics tools is a strong plus (Looker, Data Studio, or similar). - Solid understanding of SQL fundamentals; you can write simple queries and are eager to improve. - Initial exposure to Google Cloud (BigQuery, Cloud Storage, Cloud Functions, etc.) is appreciated. - Basic understanding of dbt and end-to-end data pipeline concepts (ETL/ELT). - Familiarity with Git and collaborative development workflows is a plus. - Strong interest in data visualization and the ability to build basic, clear reports with guidance. - Attention to detail and quality, with a structured and solution-oriented mindset. - Strong willingness to learn, take feedback, and continuously improve. - Curiosity about both the business context and the technical stack. - Reliability in executing tasks agreed with your mentor or consultant and communicating clearly about progress and blockers. - Team mindset: ready to help with supporting tasks such as testing, documentation, and small fixes. - You work well in a team and can progressively handle tasks independently as you gain experience. - Excellent communication and collaboration skills (with colleagues and, when relevant, with external stakeholders). - You speak Spanish and English fluently. Speaking French is a significant plus and will help you stand out from other applicants. Benefits - Be part of a dynamic team that shares strong values. - Continuous training and development of both soft and hard skills. - Flexible working hours and remote policies. - An excellent team of colleagues and regular team-building activities. - And much more. We have compiled a detailed handbook covering all you need to know about our company. Company Description At Astrafy, we are on a mission to empower every individual with a truthful vision of reality. By acting as a seamless extension of our clients' Data & AI departments, we engineer the robust foundations required to strip away bias and replace guesswork with certainty. We prioritize true craftsmanship over generic consulting, bringing strict software engineering rigor to the rapidly evolving data and Generative AI landscape. Ultimately, we don't just build technology — we democratize insights, enabling organizations to make confident, fact-driven decisions that unlock their highest potential.

• Build and maintain a unified data collection platform using Golang, Kubernetes, ClickHouse, and NATS, with success measured by reliability, performance, and adoption across GitLab teams. • Help improve the emission, transit, and quality of instrumentation data across the system, with success measured by data quality, data integrity, and usage billing accuracy. • Support usage billing and instrumentation systems during working hours, with success measured by timely incident handling and reliable service restoration. • Work across the organization with research and development teams and the enterprise data organization to deliver common solutions, with success measured by adoption across multiple stakeholders. • Contribute to technical choices that balance ease of use for product teams with reliability and correctness for data consumers, with success measured by platform usability and trusted downstream data.

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.