76 to 93 of 93 Data Ingestion Jobs in England

months (very likely to be extended) We are hiring a Lead Solution Architect for a role with a distinct 80/20 focus: 80% Data Solution Architecture: Act as the lead architect shaping an Enterprise Data Platform (EDP). You'll design scalable data ingestion pipelines … across Finance, ERP, CRM, and Supply Chain (WMS/TMS) systems, bringing best-practice patterns and coaching the technical data team without writing code. 20% Governance and ARB Facilitation: Schedule and chair the monthly Architecture Review Board (ARB). Act as a senior sounding board and sense-checker ...

designing, building, and operating production-grade ML systems from the ground up. Responsibilities include: Building and owning end-to-end machine learning solutions, from data ingestion through to deployment and monitoring Developing scalable data pipelines that process large volumes of real-time and batch data Training … production environments Working with Databricks, AWS, Python, Kafka, and modern MLOps tooling Leveraging machine learning, LLMs, and multimodal AI techniques across structured and unstructured data sources Collaborating with engineering, product, and business stakeholders to deliver impactful solutions Contributing to system architecture, platform design, and technical best practices Driving measurable ...

expansion into European markets, there's plenty to get involved in. You'll work closely with engineers and traders, building reliable backend services and data pipelines that support forecasting, trading and day to day business operations. You don't need previous energy or trading experience: curiosity, sound engineering judgement … willingness to take ownership matter most. The role Sitting between backend software engineering and data engineering, this position gives you the chance to understand how your work connects to the wider business, including cash management and financial workflows. You'll: Build and maintain data ingestion services connecting ...

implementation of a repeatable integration pattern to extract security logs from complex third-party applications into Microsoft Sentinel. - Define approaches for log collection, data ingestion and integration, leveraging Azure Data Factory where appropriate. - Design and support the initial implementation of a Data Loss Prevention (DLP) capability … application teams to translate requirements into practical technical solutions. Key experience: - Strong Microsoft Sentinel/Azure security architecture experience. - Experience designing SIEM integrations, log ingestion pipelines and custom connectors. - Knowledge and experience of Azure Data Factory and Azure integration services. - Hands-on experience designing and implementing Microsoft Purview ...

latency of AI applications and retrieval workflows. - Manage infrastructure-as-code using Terraform and support containerised deployments. - Build CI/CD pipelines and automate data ingestion, embedding generation and vector indexing. - Implement monitoring, logging, tracing and performance optimisation across AI workloads. - Apply security, access controls, versioning and governance … DevOps and security teams to deliver production-ready solutions. Skills & Experience - Strong Python development skills. - Commercial experience delivering solutions using Microsoft Azure. - Experience with data integration and ETL pipelines, such as Azure Data Factory. - Familiarity with vector databases or search technologies, such as OpenSearch. - Experience with Terraform, infrastructure ...

components, and create reusable patterns that accelerate delivery of high-value use cases. Your work will directly influence how AI is embedded into the data, knowledge and process layers of the enterprise, ensuring solutions are robust, compliant and commercially viable. Key Responsibilities: Architect end-to-end AI solutions across … data, knowledge and process layers, covering internal business processes, reporting, frontline operations and customer experience. Design and deliver proof-of-concept AI solutions that validate target architectures, use cases and reusable patterns at enterprise scale. Define and document AI solution blueprints, including integration patterns for APIs, microservices, orchestration ...

components, and create reusable patterns that accelerate delivery of high-value use cases. Your work will directly influence how AI is embedded into the data, knowledge and process layers of the enterprise, ensuring solutions are robust, compliant and commercially viable. Key Responsibilities: Architect end-to-end AI solutions across … data, knowledge and process layers, covering internal business processes, reporting, frontline operations and customer experience. Design and deliver proof-of-concept AI solutions that validate target architectures, use cases and reusable patterns at enterprise scale. Define and document AI solution blueprints, including integration patterns for APIs, microservices, orchestration ...

government agencies worldwide. Our mission is to help the innovation community make better decisions faster, with greater confidence, combining the worlds most trusted patent data with sophisticated analytics, AI-powered insights, and purpose-built workflows. Protégé in PatentSight is our clients next-generation agentic AI assistant, purpose-built … strategic patent analysis. Protégé replaces complex filter-based workflows with natural language questions, surfacing structured, decision-ready insights grounded in trusted data and established metrics. About the role: We are seeking a Senior Cloud & AI Security Enablement Engineer to provide hands-on cloud security engineering capability while also enabling ...

will own the overall finance solution design for financial services and insurance customers. You will translate finance outcomes into decisions about processes, accounting, data and systems, and guide teams through delivery. Alongside customer engagements, you will shape opportunities and strengthen our sector capability through reference designs, reusable assets … trade-offs and readiness gaps clear to customer sponsors. Own the end-to-end Financials design, with depth in record to report, the Foundation Data Model (FDM), chart of accounts, work tags, multi-entity and multi-currency accounting, intercompany and reporting. Define how Workday Financials, Prism Analytics and Accounting ...

considering The continued digitisation of our clients' businesses and the growing complexity of modern technology estates generate vast volumes of data and telemetry. The real value lies in making sense of those signals, building a coherent view of service health and business impact, and turning insight into operational intelligence. … into clear architectural decisions. Lead the end-to-end architecture of the Splunk platform, including scalability, resilience, security, performance, and lifecycle management. Define telemetry, data-ingestion and integration patterns across applications, infrastructure, cloud, networks and service management. Own architecture governance for the observability domain, including HLDs, reference architectures ...

guiding a team? A market-leading business in Central London is seeking a Hands-on Analytics Engineering Lead (Player-Coach) to own downstream data transformation, standardise metric layers, and lead/mentor a dedicated team of two Analytics Engineers. With core cloud infrastructure and data platform management handled … globally by HQ in Germany, this role is dedicated to maximizing value from the data building scalable models, championing software engineering best practices within analytics, and bridging the gap between technical data layers and commercial decision-makers. The Role: Hands-on Technical Leadership: Design, build, and optimize production ...

modular, maintainable and built to scale, following secure development principles. Governance: Implement solutions in line with our AI governance framework, covering areas such as data handling, audit logging, human-in-the-loop controls and regulatory compliance. Cost Management: Monitor and optimise LLM API usage and infrastructure costs, implementing strategies … vector databases, including context windows, temperature and sampling parameters, system prompts and tool/function calling. Experience implementing RAG pipelines end-to-end, including data ingestion, chunking strategies, embedding model selection and retrieval tuning. Experience implementing parsing pipelines for tasks such as document processing and ingestion, including ...

customer growth, marketing effectiveness, pricing and personalisation.You will work with some of ASOS's richest datasets, including customer behaviour, transactions, marketing interactions and product data, turning these into production-grade machine learning systems that deliver measurable value for customers and the business.Working alongside Applied Scientists, Data Engineers … learning systems that support customer engagement, marketing effectiveness, pricing and commercial decision-making.Own the end-to-end engineering lifecycle of machine learning products, including data ingestion, feature engineering, deployment, monitoring and optimisation.Productionise advanced machine learning solutions and ensure they operate reliably at ASOS scale.Partner closely with Applied Scientists ...

premises environments, adapting your approach to each environment's security and connectivity constraints Taking end-to-end ownership of production pipelines, from raw data ingestion through to live inference Building the monitoring, evaluation and guardrail tooling that shows how a system is actually performing in the field Setting … right call Real-world experience deploying AI/ML systems into production, beyond notebooks and proof-of-concepts Confidence across inference performance, data pipeline design, state/memory handling, and tool or function calling Experience building retrieval and search over very large, multi-modal datasets, including indexing and embedding ...

premises environments, adapting your approach to each environment's security and connectivity constraints Taking end-to-end ownership of production pipelines, from raw data ingestion through to live inference Building the monitoring, evaluation and guardrail tooling that shows how a system is actually performing in the field Setting … right call Real-world experience deploying AI/ML systems into production, beyond notebooks and proof-of-concepts Confidence across inference performance, data pipeline design, state/memory handling, and tool or function calling Experience building retrieval and search over very large, multi-modal datasets, including indexing and embedding ...

models, translating techniques such as sequence prediction, intent modelling and imitation learning into production ready systems.You'll build end-to-end AI pipelines spanning data ingestion, feature engineering, model training, inference and monitoring, while applying causal inference to understand the real world impact of AI driven decisions.Collaborating with … good understanding of causal inference and techniques for evaluating the impact of AI driven decisionsYou have experience building end-to-end ML pipelines, including data processing, feature engineering, training, inference and monitoringYou have strong engineering skills, with experience integrating AI services into production platforms using APIs, microservices or event ...

translating techniques such as sequence prediction, intent modelling and imitation learning into production ready systems. You'll build end-to-end AI pipelines spanning data ingestion, feature engineering, model training, inference and monitoring, while applying causal inference to understand the real world impact of AI driven decisions. Collaborating … understanding of causal inference and techniques for evaluating the impact of AI driven decisions You have experience building end-to-end ML pipelines, including data processing, feature engineering, training, inference and monitoring You have strong engineering skills, with experience integrating AI services into production platforms using APIs, microservices ...

systems and methodologies. Identity based threat detection and prevention. Privileged Access and Session Management SIEM Management: Design, implement, and maintain of workspaces, including data connectors, Logic App, Function App, analytics rules, workbooks, and playbooks. Develop and refine custom queries for advanced threat hunting, incident investigation, and reporting. Optimize SIEM … performance, cost, and data retention policies Identify new log sources work closely with infrastructure teams Identify, onboard, and configure critical security log sources with a focus on critical infrastructure services such as Active Directory (Domain Controllers, ADFS), network devices, firewalls, servers (Windows/Linux), and cloud infrastructure logs. Manage ...