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.

Role Description As a Product Analytics Engineer at Nous Research, you'll own the measurement systems that help us understand how users interact with Hermes Agent. You'll build the analytics foundation across our products—from instrumentation and event pipelines to dashboards and experimentation—then use that data to identify opportunities to improve activation, engagement, retention, and long-term product success. You'll partner closely with Product, Engineering, Design, Support, and Leadership to turn behavioral insights into concrete product improvements. This role is ideal for someone who enjoys building reliable analytics infrastructure while also using data to influence product strategy and execution. Responsibilities - Own product analytics end-to-end, from event design and instrumentation through data modeling, analysis, and product recommendations. - Define and maintain a consistent event taxonomy and shared metrics layer across Hermes Agent and Nous Portal. - Implement and maintain analytics instrumentation across desktop, mobile, web, CLI, backend services, and third-party integrations. - Build reliable data pipelines, transformations, dashboards, and monitoring systems that make product behavior easy to understand and trust. - Analyze user funnels, cohorts, retention, behavioral paths, and churn to identify friction points and opportunities for improvement. - Segment user behavior across platforms, acquisition channels, pricing plans, models, tools, and use cases to uncover actionable insights. - Design and evaluate experiments, measuring the impact of product changes on activation, engagement, retention, conversion, and revenue. - Partner with Product, Engineering, Design, and Support to translate data into prioritized product improvements. - Combine quantitative analysis with qualitative feedback from users, customer conversations, and direct product usage to develop a complete understanding of user behavior. - Build monitoring and alerting systems for key product metrics and proactively investigate anomalies. - Establish best practices for analytics instrumentation, documentation, data quality, and privacy-conscious telemetry. Qualifications - 5+ years of experience in Product Analytics, Analytics Engineering, Data Engineering, or a similarly technical product role. - Expert SQL skills and strong proficiency in Python, with experience working in production application codebases using TypeScript, JavaScript, or similar languages. - Hands-on experience implementing analytics instrumentation across client applications and backend systems. - Experience with modern product analytics platforms such as PostHog, Amplitude, or Mixpanel, along with data warehouses and BI tools. - Deep understanding of product metrics including activation, engagement, retention, churn, experimentation, and funnel analysis. - Strong analytical and problem-solving skills with the ability to trace issues from dashboards through underlying systems and instrumentation. - Excellent communication skills and the ability to translate complex behavioral data into clear product recommendations. - Entrepreneurial mindset, strong ownership, and the ability to operate effectively in a fast-moving environment. - Extensive use of AI-assisted development and analysis to improve speed, depth, and quality of work. Nice-to-Have - Experience working on AI products, LLM applications, AI agents, or developer tools. - Familiarity with agent workflows, tool calling, model routing, memory systems, and other modern AI application patterns. - Experience measuring cross-platform products spanning desktop, mobile, web, CLI, and enterprise deployments. - Experience with subscription or usage-based SaaS products, including conversion, credits, renewals, and monetization. - Experience designing privacy-conscious telemetry and analytics systems for open-source or developer-focused products. - Experience building analytics systems that support high-volume event streams and rapidly growing products.

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.

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.