1 to 25 of 137 Use Case Jobs in Central London

modern data engineering tech stack and working knowledge of modern database (SQL, NoSQL) with Google Cloud Key responsibilities: Product knowledge transfer: Document existing product knowledge including use case, usage metrics, business processes, technical spec and documentation Document non-functional product knowledge Business analysis: Analyze AS-IS product landscape, use cases, business processes, and customer needs … Fulfil Product Manager responsibility during product development phase. Attend planning sessions, stand-ups, and Agile ceremonies Key skills/knowledge/experience: 8+ Years Experience Business use case analysis User interviews Stakeholder mapping Requirements documentation writing Working knowledge of software product development Working knowledge of Cloud Excellent verbal and written communication Proven agile development experience Experienced user More ❯

identification and delivery of opportunities to apply Generative AI and Agentic AI tools across business and operational processes Collaborate with business stakeholders and technology partners to assess potential use cases for AI adoption and automation Support the implementation of AI-driven solutions within cloud or SaaS ecosystems Maintain awareness of emerging technologies, particularly around AI and digital transformation More ❯

databases, and streaming data. Optimize performance, scalability, and cost efficiency of Databricks clusters and workflows. Collaborate with cross-functional teams to support analytics, machine learning, and business intelligence use cases. Implement data governance, lineage, and observability best practices using tools such as Unity Catalog, DataHub, or Collibra. Mentor junior engineers, fostering best practices in data engineering, testing, and More ❯

Work closely with cross-functional teams — HR, IT, and Data Governance — to ensure data consistency and compliance with GDPR and privacy standards. Support HR reporting and workforce analytics use cases, including attrition, diversity, headcount, compensation, and talent management analytics. Key Skills & Experience: Technical Skills: Deep expertise in SAP Datasphere/SAP Data Warehouse Cloud Strong experience in SAP More ❯

masking, and policies/entitlement understanding Build and optimise ELT pipelines (using tools such as dbt, Airflow, Fivetran, or native Snowflake tasks) to support batch and real-time use cases Collaborate with Kubrick and client stakeholders to inform delivery planning, data strategy, and architecture decisions Promote engineering excellence through code reviews, reusable patterns, and contribution to Kubrick’s More ❯

. Develop robust pipelines for real-time and batch data ingestion from diverse and complex sources. Model and optimise data for performance, visibility, and downstream analytics/ML use cases. Champion best practices: CI/CD, TDD, GitOps, observability, schema validation, and data quality. Collaborate with data scientists and ML engineers to deploy production-grade AI/ML More ❯

global 3PD forums and strategy sessions Technical & Operational Excellence Perform advanced data profiling and analysis of third-party data sources to validate quality, coverage, and fitness for business use cases Capture and document metadata, data lineage, transformation rules, and business definitions for all external data sources in enterprise metadata repositories and data catalogs Develop and maintain technical specifications More ❯

Finance/Telecomm/LSH/Manufacturing/Retail domain. Prior experience in identifying new opportunities to optimize the business through analytics, AI/ML and use case prioritization. The individual should be a thought leader having a well-balanced analytical business acumen, domain, and technical expertise. Large Language Model Expertise: Experience in working with and fine More ❯

analyse, and document business requirements. Translate business needs into clear and concise functional specifications. Facilitate workshops, interviews, and meetings to gather insights and drive alignment. Develop process models, use cases, user stories, and workflow diagrams. Work closely with product owners to prioritize requirements and manage backlogs. Support the development and testing teams by clarifying requirements and ensuring alignment More ❯

the development and implementation of AI solutions across portfolio companies to drive operational efficiency and growth. Collaborate with internal teams and portfolio company management to identify high-impact use cases for AI tools. Oversee AI/ML model development, deployment, and monitoring, ensuring scalability and robustness. Conduct data analysis, experimentation, and validation to continuously improve AI systems and More ❯

datasets from multiple sources (investment, risk, client, operational) to create integrated analytical views. Contribute to the development of a modern data platform supporting advanced analytics and machine learning use cases. Support the migration of legacy reporting tools into Databricks and modern BI solutions. Key Skills & Experience Essential: Strong hands-on experience with Databricks (SQL, PySpark, Delta Lake). More ❯

team of data scientists and collaborating with engineering and product leaders. Key Responsibilities Drive end-to-end delivery of data science solutions for digital banking and risk analytics use cases. Build predictive models for credit risk, fraud prevention, and customer behaviour using cutting-edge ML techniques. Partner with product teams to embed intelligent decision engines into core banking More ❯

Company Market leading SaaS organisation building out their AI function. About the Role This project is a greenfield build out of AI capabilities. They are starting with RAG use cases as a low bar, but are targeting a rich Agentic implementation in the near term. The incumbent has an opportunity to work on the foundational architectural definition and More ❯

major insurance client engagement . The role focuses on scaling a Snowflake Data Warehouse and expanding its DBT Cloud modelling capabilities to support new analytics and regulatory data use cases across the business. Assignment Details Initial Duration: 6–12 months (until March 2026, likely extension given scope) Location: Hybrid – minimum of 2 days per week in London Day More ❯

highest level. Drive the development and adoption of scalable, automated data science tooling and frameworks. Explore and integrate emerging AI technologies, such as LLMs and Agentic AI, taking use cases from proof-of-concept through to production. Champion best practices in experimentation, causal inference, and uplift modelling. Own and deliver the most complex analytical projects, translating ambiguous questions More ❯

ingestion pipelines and transformations within the Quantexa platform using Spark and Scala. Configure and implement Quantexa components such as Entity Resolution, Scoring, and Network Generation to support specific use cases. Collaborate with Tech Leads and Solution Architects to design scalable and performant Quantexa solutions. Translate business and technical requirements into efficient, production-ready data engineering solutions. Support the More ❯

Working knowledge of data modelling, views, and performance tuning. SQL: Proficient in writing, optimising, and troubleshooting queries. Azure Data Lake: Understanding of data storage and structure for analytics use cases. Git/Azure DevOps: Familiar with version control and Agile delivery workflows. Microsoft Fabric (Desirable): Awareness or early exposure to Fabric data pipelines, dataflows, and workspace management. Soft More ❯

consultants to design and deliver technology-enabled transformation. • As a Business Analyst , you will engage directly with stakeholders to capture business requirements and translate them into actionable outcomes. • Use your analytical skills to identify opportunities for improvement and shape solutions that enhance operational performance. • Apply Agile delivery methods to deliver tangible value quickly and iteratively. • Contribute to the … Proven experience as a Business Analyst or in a similar analytical or consulting role. • Strong understanding of business analysis methods, including process modelling, requirements elicitation, and use case development. • Experience delivering within Transformation or complex delivery programmes. • Proficiency with Agile methodologies and frameworks such as Scrum, Kanban, SAFe, or LeSS. • Ability to analyse and interpret complex information More ❯

Integrate data from diverse sources including cloud warehouses, APIs, and operational systems Define semantic layers using dbt and Delta Live Tables to ensure consistency across analytics and AI use cases Enable Generative AI and ML workloads by designing pipelines for vector search, RAG, and feature engineering Implement secure access and governance controls including RBAC, SSO, token policies, and More ❯

opportunities. Translate complex business needs into clear, testable IT system requirements and user stories. Lead requirements analysis across Agile, Waterfall, and Iterative project methodologies. Produce detailed documentation including use cases, UML diagrams, UI mockups, and more. Drive the successful delivery of new systems and features, supporting implementation and user adoption. Collaborate with solution architects and subject matter experts More ❯

environment. Key Responsibilities: Build and maintain reliable, scalable data pipelines for structured, semi-structured, and streaming data Design and improve data models to support analytics and machine learning use cases Develop and support real-time data workflows using technologies such as Apache Kafka Monitor and ensure data quality, reliability, and security across the stack Contribute to the evolution More ❯

ll Need 6+ years of professional software engineering experience. Strong programming background in Python or Go, plus another object-oriented language. Proficiency in SQL (both transactional and analytical use cases). Experience working with data lakes, ETL frameworks, and orchestration tools such as Airflow. Familiarity with streaming systems (Kafka) and metadata management tools. Solid knowledge of cloud environments More ❯

Power BI, Tableau, or Python-based visualization tools. Communicate findings to both technical and non-technical stakeholders effectively. Partner with business analysts, architects, and domain experts to define use cases and success metrics. Contribute to the enterprise AI roadmap, bringing thought leadership on analytical methodologies. Document methodologies, model logic, and validation results for audit and reproducibility. Participate in More ❯

Cloud, DevOps, Cybersecurity, Software Engineering and more. In this Kubernetes-focused role, you'll help build and scale a bare-metal HPC platform for a broad spectrum of use cases – from latency-sensitive trading to big data and analytics – with the opportunity to expand into cloud where appropriate. What you’ll do: Design and manage highly available Kubernetes More ❯

innovation. You will provide the content of our proprietary investment framework directly to our clients. In order to succeed, you are required to deep dive and analyze various use cases with different teams like investment, finance, data or strategy engineers. Apart from supporting our constantly evolving products by driving the development of our components, you will actively help More ❯