26 to 32 of 32 Data Structures Jobs in Scotland

years of software engineering experience with knowledge of HTML, CSS, TypeScript and ideally modern frontend frameworks. Logic & State: Understanding of application state patterns, data flows (e.g., Pinia, Vuex, or Redux) and reactivity/observables. API & Infrastructure: hands-on experience with RESTful API, websockets. Solid understanding of web development principles. … Engineering Mindset: a good foundation in data structures/algorithms and design patterns. Ability to see the long-term implications of solutions. Collaboration: Demonstrated team player skills and a willingness to work with others. Desired Skills Resilient Systems: excited about building, operating, and maintaining resilient, scalable systems. Tests ...

Skills: Proficiency in Python or Java for backend developmentStrong understanding of AI concepts and practical applicationExperience with distributed systems architectureAbility to design and optimize data models and data structuresDemonstrated skill in streamlining engineering processesKnowledge of industrial hygiene principles in software environmentsExperience integrating Claude AI or similar advanced … abilitiesPreferred Qualifications, Capabilities, and Skills: Experience leading software engineering teamsFamiliarity with cloud platforms and microservicesAdvanced knowledge of backend frameworks and toolsExperience with real-time data processing and streamingBackground in security engineering, distributed systems, or program analysisExposure to DevOps practices and automationPassion for continuous learning and innovationJ.P. Morgan ...

Process Models, Sites, Reports and CDTs, with the ability to manage a single application through its full lifecycle. Strong understanding of relational databases, SQL, data modelling and enterprise data structures. Comfortable working day‐to‐day within blended teams of client staff and third‐party vendors, building good working ...

Process Models, Sites, Reports and CDTs, with the ability to manage a single application through its full lifecycle. Strong understanding of relational databases, SQL, data modelling and enterprise data structures. Comfortable working day‐to‐day within blended teams of client staff and third‐party vendors, building good working ...

downstream system impacts. Apply knowledge of tools within the Software Development Life Cycle to improve automation and operational stability. Gather, analyze and synthesize data from diverse sources to drive continuous improvement of software applications and systems. Proactively identify and solve technical problems, contributing to system architecture and coding hygiene. … ability to critically evaluate, validate and refine AI-generated outputs for correctness, performance and security. Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage ...

strengthening the CRM and Marketing Technology capabilities for the Postcode Lottery. You’ll take technical ownership of the Braze platform, designing scalable and data-driven customer engagement solutions across email and, over time, push, in-app, SMS, web and Content Cards. Are you an experienced Braze specialist with … team and help us build personalised, reliable and compliant customer journeys across multiple countries and propositions. Your work will directly support our marketing, product, data and engineering teams and every day at work, you’ll be doing your part for all the charities we support. What ...

downstream system impacts. Apply knowledge of tools within the Software Development Life Cycle to improve automation and operational stability. Gather, analyze and synthesize data from diverse sources to drive continuous improvement of software applications and systems. Proactively identify and solve technical problems, contributing to system architecture and coding hygiene. … ability to critically evaluate, validate and refine AI‐generated outputs for correctness, performance and security. Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage ...