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

Principal Data Engineer – AWS Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent Engineer future-ready data platforms that power financial transformation. The Role We’re looking for a Principal Data Engineer with AWS to join our growing team of engineering experts driving next -generation transformation for Tier 1 financial services clients. You’ll play a pivotal role in designing, building, and deploying cloud-based data pipelines that enable trusted, scalable data platforms. Working across greenfield initiatives and enterprise-scale programmes, your work will directly influence how data is ingested, transformed, and consumed across the financial services industry. You'll also embrace AI-enabled ways of working, using approved AI and automation tools where appropriate to enhance productivity, improve delivery quality, and accelerate engineering outcomes while applying sound engineering judgement and responsible AI practices. What You’ll Do Design and build end-to-end data pipelines using AWS -native services and modern cloud data architectures, ensuring scalable, secure, and resilient solutions. Partner with clients and cross-functional teams to understand business requirements, define technical solutions, and deliver production-grade data platforms. Apply AWS Well-Architected Principles, engineering best practices, CI/CD, and AI-enabled development approaches to improve quality, efficiency, and operational excellence. Lead the development of robust, tested, fault-tolerant data engineering solutions while promoting responsible engineering standards and governance. Mentor engineers, share technical expertise, and encourage the effective and responsible use of approved AI tools and automation to enhance collaboration and delivery. What We’re Looking For Strong proficiency in Python , Scala , or Java , with hands-on experience of Big Data technologies including Spark , Hadoop , or similar distributed processing frameworks. Experi

Senior Data Engineer – AWS Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent Engineer future-ready data platforms that power financial transformation. The Role We’re looking for a Senior Data Engineer with AWS to join our growing team of engineering experts driving next -generation transformation for Tier 1 financial services clients. You’ll play a pivotal role in designing, building, and deploying cloud-based data pipelines. Working across greenfield projects and enterprise-scale platforms, your work will directly impact how data is ingested, transformed, and served at scale across the financial services industry. You'll also embrace AI-enabled ways of working, using approved AI and automation tools where appropriate to improve engineering productivity, accelerate delivery, and enhance solution quality while applying sound engineering judgement and responsible AI practices. What You’ll Do Design and build end-to-end data pipelines leveraging AWS -native services and modern data architectures. Collaborate with clients to gather requirements, define technical solutions, and deliver production-grade systems that meet business needs. Apply AWS Well-Architected Principles, CI/CD practices, and AI-enabled engineering approaches to deliver scalable, secure, resilient, and high-quality solutions. Develop robust, tested, and fault-tolerant data engineering solutions while promoting engineering best practices and data governance. Mentor junior engineers, contribute to knowledge sharing, and encourage the responsible use of approved AI tools and automation to improve collaboration and delivery. What We’re Looking For Strong proficiency in Python , Scala , or Java with hands-on experience in Big Data technologies including Spark , Hadoop , or similar distributed processing frameworks. Practical experience building real-time event streaming pipelines using technologies such as Kafka , Spark Streaming, or Amazon Kinesis within AWS en

Senior Azure Data Engineer ( Databricks ) Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent Engineer advanced data solutions at scale in a world-class consulting environment. The Role As a Senior Azure Data Engineer ( Databricks ) at Capco, you will play a hands-on role in designing, building, and deploying scalable and secure data engineering pipelines using the Databricks platform on Azure . You'll partner with clients to understand their data needs and develop innovative solutions that drive business transformation. You'll also contribute to engineering best practices and continuous improvement across cross-functional teams. Databricks platform on Azure . You'll embrace AI-enabled ways of working, using approved AI and automation tools where appropriate to improve engineering productivity, accelerate delivery, and enhance solution quality while applying sound engineering judgement and responsible AI practices. What You'll Do Design and develop robust data pipelines using Delta Lake, Spark Structured Streaming, Unity Catalog, and Azure -native services. Build real-time, event-driven solutions using technologies such as Kafka and Azure Event Hubs, applying AI-enabled engineering approaches where appropriate to improve delivery efficiency. Develop and maintain CI/CD pipelines using Azure DevOps, Jenkins, GitHub Actions, and modern DevOps practices to support reliable deployments. Collaborate with clients and multidisciplinary teams to translate business requirements into scalable, production-ready data solutions. Champion clean code, data lifecycle optimisation, engineering best practices, and the responsible use of approved AI tools and automation to improve collaboration and delivery. What We're Looking For Proven hands-on experience with the Databricks platform, including orchestration and enterprise-scale Azure data engineering solutions. Strong technical skills in Python , PySpark , and SQL, with experience wor

Principal Azure Data Engineer ( Databricks ) Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent Lead the architecture of data platforms driving the future of financial services. The Role As a Principal Azure Data Engineer ( Databricks ) at Capco, you'll architect and lead the delivery of enterprise-grade data solutions using the Databricks platform within the Azure ecosystem. You'll drive the design and implementation of streaming and batch data pipelines, helping our clients modernise their data capabilities. Working with cross-functional teams, you'll guide clients on technical strategy and best practices while ensuring quality, security, and governance standards are maintained across deployments. You'll also champion AI-enabled ways of working, using approved AI and automation tools where appropriate to improve engineering productivity, accelerate delivery, and enhance solution quality while applying sound engineering judgement and responsible AI practices. What You'll Do Architect and lead the end-to-end delivery of Databricks -based data platforms across Azure environments. Design secure, scalable data pipelines using Delta Lake, Spark Structured Streaming, Unity Catalog, and Azure -native services, applying AI-enabled engineering approaches where appropriate. Establish and promote engineering best practices across the data lifecycle, ensuring robust governance, quality, and operational excellence. Partner with clients to define technical strategy, data architecture, and governance frameworks that align with business objectives. Mentor engineering teams, develop internal capability, and encourage the responsible use of approved AI tools and automation to enhance delivery and collaboration. What We're Looking For Proven expertise with the Databricks platform, including Unity Catalog, Delta Lake, orchestration, and enterprise-scale Azure deployments. Strong technical skills in Python , PySpark , and distributed data pr

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