26 to 37 of 37 Data Pipeline Jobs in the East Midlands

credit analysis through to lender integration, decisioning models, and customer self-service. The environment blends custom full-stack applications, CRM, and AWS-hosted data engineering systems. This role combines hands-on coding with strategic leadership. You will design scalable architecture, improve engineering standards, and mentor a small … visibility. What You'll Do Own the technical roadmap, working directly with the Head of Tech to deliver next-generation customer and data platforms. Design and build web applications and APIs using Node.js, React, Python, and AWS. Oversee integrations between CRM, AWS services, data pipelines ...

robust engineering, governance, and scalability. Responsibilities Design, build, and deploy machine learning models into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around … skills and hands-on experience with ML libraries (TensorFlow, PyTorch, scikit-learn) Experience deploying and supporting ML models in production Solid understanding of data pipelines, versioning, testing, and software engineering best practices Experience working with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk ...

robust engineering, governance, and scalability. Responsibilities Design, build, and deploy machine learning models into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around … skills and hands-on experience with ML libraries (TensorFlow, PyTorch, scikit-learn) Experience deploying and supporting ML models in production Solid understanding of data pipelines, versioning, testing, and software engineering best practices Experience working with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk ...

robust engineering, governance, and scalability. Responsibilities Design, build, and deploy machine learning models into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around … skills and hands-on experience with ML libraries (TensorFlow, PyTorch, scikit-learn) Experience deploying and supporting ML models in production Solid understanding of data pipelines, versioning, testing, and software engineering best practices Experience working with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk ...

robust engineering, governance, and scalability. Responsibilities Design, build, and deploy machine learning models into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around … skills and hands-on experience with ML libraries (TensorFlow, PyTorch, scikit-learn) Experience deploying and supporting ML models in production Solid understanding of data pipelines, versioning, testing, and software engineering best practices Experience working with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk ...

robust engineering, governance, and scalability. Responsibilities Design, build, and deploy machine learning models into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around … skills and hands-on experience with ML libraries (TensorFlow, PyTorch, scikit-learn) Experience deploying and supporting ML models in production Solid understanding of data pipelines, versioning, testing, and software engineering best practices Experience working with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk ...

leverage artificial intelligence to drive smarter decisions. Their mission: to make enterprise AI accessible, actionable, and transformative, helping companies unlock insights from complex data in real-time. They're looking for a Founding AI Engineer to join the team, helping shape the product, technology, and AI strategy from … leadership team. What You'll Do: Design, build, and deploy AI/ML models powering the core platform. Create scalable AI infrastructure, data pipelines, and deployment workflows. Collaborate with product and engineering to turn business problems into AI solutions. Experiment with the latest AI techniques to innovate ...

growth, scaling the platform, and building a high-performing engineering team. About the Role You will take full ownership of the platform architecture, data pipelines, integrations, and multi-tenant SaaS infrastructure. This is a highly visible, strategic role where you will work closely with the founder and early … customers, ensuring the platform is scalable, secure, reliable, and enterprise-ready. Key Responsibilities Own the full platform architecture, including ingestion, scoring, data stores, APIs, and dashboards. Lead AI/ML-powered enrichment and scoring systems. Build and scale microservices, event-driven pipelines, and automated intelligence workflows. Harden cloud ...

growth, scaling the platform, and building a high-performing engineering team. About the Role You will take full ownership of the platform architecture, data pipelines, integrations, and multi-tenant SaaS infrastructure. This is a highly visible, strategic role where you will work closely with the founder and early … customers, ensuring the platform is scalable, secure, reliable, and enterprise-ready. Key Responsibilities Own the full platform architecture, including ingestion, scoring, data stores, APIs, and dashboards. Lead AI/ML-powered enrichment and scoring systems. Build and scale microservices, event-driven pipelines, and automated intelligence workflows. Harden cloud ...

growth, scaling the platform, and building a high-performing engineering team. About the Role You will take full ownership of the platform architecture, data pipelines, integrations, and multi-tenant SaaS infrastructure. This is a highly visible, strategic role where you will work closely with the founder and early … customers, ensuring the platform is scalable, secure, reliable, and enterprise-ready. Key Responsibilities Own the full platform architecture, including ingestion, scoring, data stores, APIs, and dashboards. Lead AI/ML-powered enrichment and scoring systems. Build and scale microservices, event-driven pipelines, and automated intelligence workflows. Harden cloud ...

growth, scaling the platform, and building a high-performing engineering team. About the Role You will take full ownership of the platform architecture, data pipelines, integrations, and multi-tenant SaaS infrastructure. This is a highly visible, strategic role where you will work closely with the founder and early … customers, ensuring the platform is scalable, secure, reliable, and enterprise-ready. Key Responsibilities Own the full platform architecture, including ingestion, scoring, data stores, APIs, and dashboards. Lead AI/ML-powered enrichment and scoring systems. Build and scale microservices, event-driven pipelines, and automated intelligence workflows. Harden cloud ...

growth, scaling the platform, and building a high-performing engineering team. About the Role You will take full ownership of the platform architecture, data pipelines, integrations, and multi-tenant SaaS infrastructure. This is a highly visible, strategic role where you will work closely with the founder and early … customers, ensuring the platform is scalable, secure, reliable, and enterprise-ready. Key Responsibilities Own the full platform architecture, including ingestion, scoring, data stores, APIs, and dashboards. Lead AI/ML-powered enrichment and scoring systems. Build and scale microservices, event-driven pipelines, and automated intelligence workflows. Harden cloud ...