Data Engineer

About Dot Collective We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects. About you Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. Your key skills and capabilities: · Implementing cloud-native data platforms · Engineering scalable and reliable pipelines · Good knowledge of distributed computing with Spark · Understanding of cloud architecture principles and best practices · Hands-on experience in designing, deploying, and managing cloud resources · Excellent python and SQL skills · Agile ways of working · Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform · Monitoring and performance tuning of cloud-based applications and services Nice to haves: (MLOps): Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining ML Pipelines & CI/CD – Automate end-to-end ML workflows We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform. Our promise to you We will always see you as a human being and will do our very best to support your needs and wellbeing – well-designed co-working and collaboration spaces, remote working patterns that work for you, parenting leave, sabbatical

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role The Data team manages the complete lifecycle of data for researchers - from sourcing and large-scale processing to delivering datasets that power our models. Data sits at the heart of our Research efforts and enables all other teams. As part of the Data team, you’ll work with over a million hours of video and audio data. This role exists at the intersection of applied research, data engineering, and ML infrastructure rather than being a traditional research position . You’ll build the world’s best human-centric data lake by collaborating closely with our model training teams. By understanding their requirements, you’ll extract new features and annotations that elevate our datasets. You should be passionate about enhancing model performance through high-quality, accurate datasets. Our infrastructure and pipelines are in great shape, and this role provides room to not only enhance them but also influence the team’s longer-term strategy. What we're looking for: A strong background in data-centric, applied Machine Learning, with hands-on experience improving model performance through data quality, curation, labeling, and evaluation rather than model architecture alone Experience working on the data la

We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster. This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix. What you'll do Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need Strong proficiency in Python and SQL, with a solid backend or data engineering foundation Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider Experience building data pipelines and ETL/ELT processe

About Dot Collective We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects. About you Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. A little bit about the role Over the past 18 months, The Dot Collective has successfully established a dedicated Data Architecture practice , laying the foundation for robust, scalable, and innovative data solutions. This practice underpins our commitment to delivering high-quality, data-driven outcomes for clients across diverse sectors. As we continue to grow, we are seeking a Data Solution Architect to play a pivotal role in shaping and implementing cloud native data and AI platforms that make a real impact. Your Key Skills and Capabilities Work with technical teams to clarify and refine architecture so as to maintain consistency during deliver Recognise ways to describe the structure and behaviour of applications used in a business, with a focus on how they interact with each other and with business users or actors Help the customer articulate their requirements and formulate a suitable solution architecture Proven experience of designing and building data platforms. A strong understanding of modelling data and how to make data work at scale A grasp of modern data governance is also appreciated Have an understanding of Microservices and Serverless architectures. Be able to describe the structure and behaviour of the technology platform that underpins user applications and understand on-premise, Cloud hosting and end-user compute Knowledge of open source, open standards and cloud technologies An understanding of architectural concepts, methodologies and approa

About Dot Collective We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects. About you Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. Your key skills and capabilities: Designing and implementing robust python testing automation frameworks using BDD (Behave) ETL Testing: Proven experience in testing ETL pipelines, data validation, and ensuring data quality Scripting automated tests and working collaboratively with other engineers in a continuous build environment Familiarity with CI/CD tools such as AWS pipelines, Github actions Understanding of cloud architecture principles preferably AWS and/or GCP Data Testing experience - Ability to understand data requirements and perform comprehensive data testing Understanding of data engineering Excellent PyTest and SQL skills Nice to have: Behave BDD experience We expect you to have some knowledge about best practices in designing and building scalable and performant cloud-native data platforms and be comfortable with testing them. Our promise to you We will always see you as a human being and will do our very best to support your needs and wellbeing – well-designed co-working and collaboration spaces, remote working patterns that work for you, parenting leave, sabbaticals and ability to work on personal projects. We believe that a geled team is worth its weight in gold – we will do everything we can to avoid breaking well-performing teams. Whilst continuity across every project is not always possible, we thoughtfully assemble high-performing, blended teams with the appropriate levels of exper

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. As a Lead Developer Advocate, you will serve as a critical bridge between Snowflake’s product and engineering teams and the global developer community. You will create technical content, reference implementations, demos, and programs that help SQL developers, analytics engineers, data engineers, and data teams succeed with Snowflake. You will also represent the voice of the developer internally, translating friction points and emerging workflow needs into actionable product feedback, enablement priorities, and roadmap input. What You’ll Do Define and drive the advocacy strategy Own and execute the developer advocacy strategy for a key Snowflake domain spanning SQL development, analytics workflows, and the modern data stack. Align advocacy priorities with product goals, adoption opportunities, and measurable business outcomes. Identify the highest-value technical narratives, workflows, and proof points that will accelerate developer adoption and trust. Create technical content and reference implementations Build high-quality technical content including tutorials, quickstarts, blog posts, videos, workshop materials, code samples, and opinionated best-practice guides. Design and maintain production-grade reference implementations and demos that show how to use Snowflake for re