Staff Data Engineer

Fonoa

Fonoa is the Tax Operating System for autonomous tax. AI that tracks every rule, acts on every obligation, and proves every decision, built on modular infrastructure. Fonoa’s modules cover the full indirect tax lifecycle: tax ID validation, real-time tax determination, e-invoicing, and returns. All on one shared data model and integration, with one audit trail. Each added capability makes the others stronger. Agents monitor obligations, populate returns, catch anomalies and assemble audit packs in seconds. The system does the work. Humans make the calls. That’s autonomous tax. We operate across 120+ countries, with clients going live in weeks, if not days. Trusted by Canva, Netflix, Spotify, Uber, Zoom and Booking.com. Rated 4.5/5 stars and a High Performer on G2 and 4.6/5 stars on Gartner Peer Insights. Find out more: www.fonoa.com ABOUT ENGINEERING AT FONOA Engineering is central to how we build the business. We focus on solving real customer problems, not just shipping features. We work in small, high-trust teams, with full ownership across the lifecycle, from design to production and beyond. We value: * Ownership – engineers own what they build end-to-end * Simplicity – we break down complex problems into clear solutions * Thinking Big - we innovate with modern technologies (LLMs, AI Agents, etc.) to solve meaningful problems * Quality – scalable, maintainable systems are non-negotiable * Speed & iteration – we ship fast, learn, and improve continuously * Collaboration – we win as a team, not as individuals POSITION OVERVIEW As Fonoa continues to scale globally, we are looking for a Data Engineer to help us bootstrap an internal data platform from the ground up. Working closely with the Infrastructure team, you will play a foundational role in unlocking the value hidden across our different systems and make data accessible to both technical and non-technical stakeholders in a seamless way. This is not a role where you'll walk into a mature data stack with well-defined requirements. We have data spread across multiple systems and services, and we need someone who can help us experiment, iterate, and discover how to best add value to the business and our products through data. You'll be exploring what's possible, building the first versions of pipelines and tooling, and shaping the direction of data engineering at Fonoa. This is a highly collaborative, hands-on role for someone who thrives in ambiguity, brings curiosity and proactivity, and is energised by the challenge of building something from scratch rather than maintaining something that already exists. What Will You Do Data Platform Foundations * Design, build, and iterate on the foundational data infrastructure that will become Fonoa's internal data platform * Evaluate and select appropriate tools and technologies based on our needs, scale, and team capabilities * Establish patterns and best practices for data modelling, cataloguing, and documentation, and data governance and quality standards early on Data Integration & Access * Connect and consolidate data from multiple internal systems and services into a unified, queryable layer * Build interfaces and tooling that enable non-technical users (including Product, Finance, Operations) to consume data independently * Ensure data quality, consistency, and reliability across sources through validation and monitoring Exploration & Value Discovery * Partner with stakeholders across the business to understand their data needs and identify high-impact opportunities * Prototype dashboards, reports, and data products to test hypotheses about where data can drive decisions * Help define what "data-driven" looks like at Fonoa and shape the roadmap accordingly Collaboration & Enablement * Work closely with the Infrastructure team on cloud resources, networking, and security considerations for data workloads * Partner with Finance, Operations, and Product to understand their reporting and analytical needs, and translate those into reliable, queryable data products * Share knowledge and advocate for data engineering best practices across the organisation What We Are Looking For * 5+ years of experience in a Data Engineering or similar role (Analytics Engineering, Backend Engineering with heavy data work) * Solid proficiency in SQL and at least one programming language (Python, Scala, or similar) * Experience building and maintaining ETL/ELT pipelines and working with data warehousing or lakehouse architectures * Hands-on experience with modern data stack tooling — particularly a columnar warehouse (BigQuery, Snowflake, or similar), a transformation layer (dbt or equivalent), and an ingestion/CDC tool (Airbyte, Fivetran, or similar) * Familiarity with cloud platforms (GCP preferred) and their data services * Experience with workflow orchestration tools * Strong communication skills and the ability to work with non-technical stakeholders and translate their needs into data solutions * Comfort with ambiguity and an ability to make pragmatic decisions with incomplete information * Prior experience bootstrapping a data platform or data function from scratch Bonus Points If You Have * Experience with data visualisation and BI tools (Metabase, Looker, Superset, or similar) * Background working in a product-oriented SaaS company * Experience working with financial or operational data (revenue, billing, reconciliation) * Exposure to infrastructure-as-code and DevOps practices What Success Looks Like * A first iteration of an internal data platform is running, consolidating data from key systems into a reliable, queryable layer * Non-technical stakeholders can access and explore data relevant to their work without needing engineering support for every question * Clear patterns and documentation exist for how data is ingested, transformed, and consumed * You have identified and delivered at least one high-impact data use case that demonstrably adds value to the business or product API DOCUMENTATION For engineers, API design and structure are an important part of evaluating a role. You can explore our API and how we build products here: https://docs.fonoa.com/ TECH STACK We use these technologies today, but we don’t hire for specific tools. We care about engineers who can understand problems, make good technical decisions, and choose the right tools for the job. * Backend: Node.js, Go * Frontend: React, TypeScript * Infrastructure: GCP, k8s, Terraform, Postgres Note: If you don’t think you have the full experience we’re looking for, but you could be a fit and are willing to learn, do apply anyway! We are building a diverse and inclusive team. As part of the recruitment process at Fonoa, we process your personal data in accordance with our Privacy Notice for Job Applicants. This notice explains how and why your data is collected and used, and how you can contact us if you have any concerns.

Marshmallow

We’re on a mission to make migration easy. We started building Marshmallow in 2017. Since then, we’ve grown from 3 to 700+ people, gained unicorn status, raised ~£140M over three funding rounds, turned profitable, insured millions of drivers and lent millions in car loans. But we’re only just getting started. Our goal is to become one of the largest financial services providers in the world. Over the next 10 years we’ll grow exponentially, not only by scaling our existing products, but also by building new ones. To achieve our goals we need incredibly ambitious, commercially driven people who never settle for ‘good enough’. Marshmallowers are hungry for autonomy and ownership, and would rather improve than coast. Everyone raises standards and has an impact, with a focus on collective success over self-interest. We’ve created an environment where curious, tenacious people win and grow together. If that sounds motivating, this could be the place for you. LONDON (HYBRID, 3 DAYS IN OFFICE) DATA SCIENCE AT MARSHMALLOW Our Data Science team partners across the business to turn data into better decisions, smarter products, and simpler customer journeys. We work closely with Product, Engineering, and Operations to build and ship models and AI systems that are reliable in production and deliver measurable impact. Within Data Science, this role sits in Claims, supporting the function and the broader ambition to automate more of the claims journey. Claims is one of Marshmallow's most important customer touchpoints, and we're looking for a Staff Data Scientist who can provide technical leadership across traditional ML and Generative AI, bring system-level thinking to how we scale decisioning, and confidently challenge proposals to ensure we build robust, sustainable solutions. WHAT YOU'LL BE DOING * Provide technical leadership for data science across Claims Fraud, shaping the approach to risk decisioning and fraud detection in partnership with Product and Engineering * Design, build and iterate on production ML and Generative AI/LLM systems that support claims validation and automation * Collaborate closely with other Claims data scientists to bring system-level thinking to how models, data and workflows fit together, identifying architectural improvements needed to scale decisioning and reduce time-to-production * Be vocal about the platform and tooling investments needed (monitoring, feedback loops, QA) to achieve AI-driven end to end claims automation * Advocate for robust, scalable, and strategically aligned technical solutions in cross-functional discussions, ensuring current systems and infrastructure contribute to the multi-year vision for automated claims handling * Set a high bar for statistical rigour, experimentation and measurement, helping improve how Claims performance and uncertainty are understood and communicated to senior stakeholders WHO YOU ARE * You think in systems: you can connect the dots between data science, engineering, and product to shape scalable solutions that build on each other over time. * You're confident in challenging assumptions and pushing for the right approach, using strong communication skills to influence stakeholders across seniority levels and disciplines with clear, pragmatic reasoning. * You thrive in ambiguity and change, staying resilient and effective during transitions while bringing structure, clarity, and momentum to complex problem spaces. * You're motivated by real-world impact, partnering closely with cross-functional teams to drive meaningful automation and better customer outcomes across the claims journey. WHAT YOU'LL BRING * Significant commercial experience delivering end-to-end Machine Learning solutions, from problem framing and experimentation through to production deployment and ongoing monitoring * Hands-on experience building and shipping Generative AI systems in production (not just prototypes), including evaluation, safety/quality considerations, and integration into customer or operational workflows * Strong statistical and modelling foundation, with experience in risk-based decisioning under uncertainty (e.g., fraud, credit, insurance, or other regulated domains) * Proven ability to influence technical direction across Data Science and Engineering, including shaping scalable model/service integration patterns and challenging proposals to drive robust, long-term solutions * Strong stakeholder management skills, with confidence communicating trade-offs and pushing back constructively with Product and Engineering to ensure high-quality outcomes PERKS OF THE JOB * Bonus scheme designed to reward high performance * Private medical insurance with Vitality, mental health support with Oliva * Personal learning budget and 2 dedicated L&D days a year * Monthly flexible benefits budget to spend as you choose * 25 days holiday plus bank holidays * 4 weeks Work From Anywhere per year We are able to offer visa sponsorship for this position. OUR PROCESS * Initial call with a member from our Talent Team (30 mins) * Past Experience interview with Hiring Manager (60 mins) * Systems Design & Technical interview with a couple of the team (90 mins) * Culture interview (60 mins) Diversity of thought We know the best ideas come from having different perspectives in the room - and we're committed to hiring fairly, regardless of background, identity or experience. If you see yourself in this role, we'd encourage you to apply.

XYZ Reality

About Us At XYZ Reality, we are a well-established, award-winning Series-A start-up accelerating toward our next funding round. Our mission is to expand our platform, enhancing features, performance, and scalability while revolutionizing the construction industry. We are a multi-disciplinary, fast-paced company working across diverse domains, including cloud development, data governance and processing pipelines, electronics, embedded software/hardware, mechanical design/manufacturing, AI & computer vision, and data science—all powering our BIM Platform. To drive this mission, we are seeking a Data Engineer experienced in data modelling, databases and data pipelines to support our existing tech stack as well as developing new features with performance, scalability in mind. You will work closely with our API/backend development and data pipeline team to create robust and efficient solutions. Responsibilities · Design, develop, and maintain dagster-based data pipeline using Python. · Design and implement efficient data models accommodating the planned product features and application requirements. · Develop SQL queries and procedures to be used by data pipeline and API services. · Debug, maintain and improve our existing codebase. · Develop and execute unit tests and integration tests to ensure software reliability. · Conduct performance profiling and stress testing to optimize system responsiveness. · Maintain clear, structured documentation for data models and ETL/ELT pipelines and codebases. · Collaborate closely with cross-functional teams, including client applications and cloud teams. · Stay adaptable, learning new technologies and contributing to various technical areas as needed. Required Skills & Experience · Bachelor’s degree in computer science or a related field or equivalent proven experience in database and data pipeline development. · Hands-on experience with code driven orchestration tools such as Dagster or Airflow · Solid experience with relational databases and SQL, preferably PostgreSQL. · Strong Python language and OOP skills. · Experience in data modelling for both transactional systems and analytical systems. · Strong debugging, troubleshooting, and performance optimization skills. · Proficiency with Git, including active participation in code reviews. · Excellent communication and teamwork skills. · Keen in developing in-house tech stacks as well as utilizing off-the-shelf components to build a robust solution. Preferred Qualifications · Familiarity with CI/CD pipelines, such as GitHub Actions and Liquibase. · Knowledge of REST/GraphQL or other API design methodologies. · Familiarity with working in Linux based environments. · Experience with Docker and Kubernetes for container orchestration. · Experience in Test-Driven Development (TDD), PyTest and software design patterns. What We Offer 🏝️ 25 days annual leave + public holidays 🩺 Private healthcare with Vitality 🎄 Christmas shutdown days on top of leave allowance (2-4 per year usually) 🚇 Office located within a 5-minute walk from Angel station 🏠 Hybrid working 🪙 Biannual salary reviews 🥳 Summer & Christmas staff parties 🍣 Free lunch bought in and after-work gathering/drinks every other Thursday in the office 💰 Employee referral scheme 🚀 Make a real-world impact of revolutionising the construction industry If you'd like to see the products and technology we have created so far on our journey you can view it in action through our YouTube and Website