AI Analytics and Visualization Engineer

Application Performance Monitoring Lead Specialist  VP2

AVP, Principal Software Engineer (Senior Technical lead)

Enterprise Analytics (AI) – TDM - Transformation Lead

Senior Analyst, Threat Detection and Response

Software Engineer – Ag & Trade

Enterprise Analytics – Machine Learning Ops/AI Projects (VP1)

VP, Engineering Manager

Lead Quality Automation Engineer

Consultant, Data Analytics & Reporting-Food

Role Description: <ul><li>The AI Analytics &amp; Value Realization Engineer is responsible for ensuring AI initiatives deliver measurable business value across ICT Engineering.</li><li>The role establishes value measurement frameworks, validates benefits, develops performance dashboards, and enables data-driven decision making across the AI portfolio. This position serves as the primary subject-matter expert for AI adoption measurement, business impact reporting, value realization tracking, and portfolio analytics</li></ul> Responsibilities: Value Definition &amp; Business Case Support <ul><li>Partner with AI Transformation Engineers during opportunity assessments.</li><li>Establish baseline metrics, value hypotheses, and expected business outcomes.</li><li>Define standardized measurement methodologies and evidence requirements for AI initiatives, distinguishing between forecast, validated, realized, and sustained business value.</li><li>Develop approaches for measuring engineering productivity and operational benefits, including time savings, cycle-time reduction, quality improvement, throughput, and adoption where direct financial measurement is not feasible.</li><li>Challenge assumptions and ensure value estimates are fact-based and measurable.</li></ul> Portfolio Measurement &amp; Reporting <ul><li>Develop and maintain AI portfolio dashboards and KPI reporting.</li><li>Track solution adoption, utilization, and business impact.</li><li>Collect and analyze deployment performance data.</li><li>Ensure consistent reporting across all AI initiatives.</li><li>Generate monthly reporting for ICT Engineering leadership, ICT AI leadership, and segment AI leadership.</li></ul> Value Realization &amp; Validation <ul><li>Validate achievement of project objectives and business benefits.</li><li>Monitor sustainability of realized benefits after deployment.</li><li>Identify underperforming initiatives and recommend corrective actions.</li><li>Support prioritization decisions using objective performance and value data.</li><li>Develop standardized value realization methodologies and reporting processes.</li><li>Design measurement approaches that compare pre- and post-deployment performance and provide credible evidence that observed improvements are attributable to deployed solutions.</li></ul> Advanced Analytics <ul><li>Perform portfolio analytics and trend analysis.</li><li>Support executive decision-making with actionable insights.</li><li>Maintain data quality and governance standards for AI program reporting.</li><li>Build Power BI dashboards and reporting solutions.</li></ul> Requirements: Experience &amp; Qualifications <ul><li>Bachelors degree in Engineering, Data Analytics, Business Analytics, Statistics, or related field.</li><li>Experience with analytics and visualization tools such as Power BI, including dashboard development, KPI reporting, and data analysis.</li><li>Strong analytical and quantitative problem-solving skills.</li><li>Experience developing and maintaining business metrics and measurement frameworks.</li><li>Experience establishing performance baselines and designing measurement approaches to evaluate the impact of implemented solutions.</li><li>Ability to translate complex data into actionable business insights.</li><li>Knowledge of engineering, technology, or transformation programs preferred.</li><li>Strong communication and executive presentation skills.</li></ul>

Responsibilities: <ul><li>Administer and support enterprise monitoring platforms and tools.</li><li>Define and implement monitoring standards, metrics, thresholds, and alerts.</li><li>Develop and maintain monitoring dashboards and reporting solutions.</li><li>Monitor application performance, system health, and service availability across enterprise environments.</li><li>Analyze monitoring data, identify trends, and proactively address potential issues.</li><li>Troubleshoot monitoring platform issues and work closely with support teams to resolve incidents.</li><li>Collaborate with application, infrastructure, and operations teams to improve monitoring coverage and effectiveness.</li><li>Drive continuous improvement initiatives in monitoring and observability practices.</li></ul> Requirements: <ul><li>Minimum 12 years of overall IT experience.</li><li>6-9 years of hands-on experience in Application Performance Monitoring (APM) or Observability.</li><li>Strong administration experience with monitoring tools such as:&nbsp;</li><li>Geneos</li><li>Grafana</li><li>Prometheus</li><li>Dynatrace and/or Datadog</li><li>AWS monitoring services</li><li>Experience creating and maintaining dashboards using Grafana, Power BI, SharePoint, or similar platforms.</li><li>Strong understanding of application performance, availability, capacity, and infrastructure monitoring.</li><li>Experience configuring monitoring rules, thresholds, alerts, and notification workflows.</li><li>Knowledge of incident management and ticketing tools such as Remedy and JIRA.</li><li>Strong troubleshooting, analytical, and stakeholder management skills.</li></ul>

Responsibilities: <ul><li>Lead the development effort for cloud-native applications across the Caching Solutions and Rewards System teams, ensuring timely execution against committed business outcomes.</li><li>Drive business commitments by aligning scope, sequencing, and technical approach with Product Management, and ensuring delivery plans are realistic, transparent, and measurable.</li><li>Design and implement continuous integration and continuous delivery (CI/CD) processes to deliver applications to production, fostering a culture of continuous process improvement.</li><li>Provide hands-on technical leadership through architecture/design reviews, code reviews, and guidance to engineers to ensure compliance with standards and best practices.</li><li>Perform Technology Alternate Assessments and create Proofs-of-Concept (as necessary) to validate options and inform technical decisions.</li><li>Work collaboratively with Product Management and Platform Engineering teams during development, launch, and continuing refinement of products iteratively.</li><li>Collaborate with internal technical resources and third-party vendors to resolve issues, understand</li><li>underlying causes, and implement sustainable solutions.</li><li>Work with team members to design, architect, and implement solutions across geographic locations, ensuring effective coordination and consistent engineering execution.</li><li>Coordinate and communicate status across stakeholders, and report delivery progress, risks, and dependency needs to leadership on a regular cadence.</li><li>Maintain deep hands-on technical knowledge by evaluating trends in modern software development practices; continuously learn and stay at the leading edge of industry trends.</li></ul> Requirements: <ul><li>Bachelor’s Degree with 8+ years of system engineering experience, or in lieu of a degree 10+ years of skilled system engineering experience.</li><li>8+ years of Strong hands-on development experience in Java and Spring Boot for building enterprise-grade services.</li><li>5+ years of Proven expertise in designing and implementing cloud-native applications using a microservices-based architecture.</li><li>Solid knowledge of event streaming and processing patterns using Kafka.</li><li>Experience deploying and operating applications on cloud platforms such as AWS and PCF (Pivotal Cloud Foundry).</li><li>Strong understanding of data storage and caching concepts and implementations using GemFire, Redis &amp; Elastic cache.</li><li>5+ years of Working knowledge of database design and persistence using MySQL, Aurora SQL &amp; no SQL.</li><li>Experience with observability, logging, and production monitoring, including tools such as Splunk and New Relic</li></ul>

Responsibilities: <ul><li>Lead end-to-end delivery of technical projects across cloud, AI, data, and enterprise platforms.</li><li>Collaborate with cross-functional teams including developers, architects, DevOps, and product managers.</li><li>Define project scope, timelines, resource plans, and delivery milestones.</li><li>Manage risks, dependencies, and change requests throughout the project lifecycle.</li><li>Ensure technical solutions meet business requirements and quality standards.</li><li>Facilitate agile ceremonies, sprint planning, and retrospectives.</li><li>Track progress using tools like Jira, Confluence, or Azure DevOps.</li><li>Communicate status updates and delivery metrics to stakeholders and leadership.</li><li>Support onboarding and coordination of external vendors or offshore teams..</li></ul> Requirements: <ul><li>Proven experience in technical project or delivery management</li><li>Strong understanding of software development lifecycle (SDLC) and DevOps practices.</li><li>Familiarity with cloud platforms (AWS, Azure, GCP) and modern infrastructure.</li><li>Excellent communication, stakeholder management, and problem-solving skills.</li><li>Experience with agile methodologies (Scrum, Kanban) and project tracking tools.</li><li>Ability to manage multiple projects and priorities in a fast-paced environment.</li><li>Experience with AI/ML, data platforms.</li><li>Certifications such as PMP, Scrum Master, or AWS/Azure Cloud Practitioner.</li><li>Exposure to hybrid cloud/on-prem environments and security/compliance frameworks.</li></ul>

Responsibilities: <ul><li>Continuously monitor security consoles and dashboards (SIEM, EDR, etc.) for suspicious activity; triage alerts to identify valid security incidents versus false positives and prioritize response based on asset criticality and business risk.</li><li>Investigate suspicious activities and security events, determine the scope and severity of incidents, and gather relevant evidence. Perform root cause analysis to identify attack vectors and affected systems.</li><li>Execute incident response actions end-to-end – including timely containment of threats, eradication of malicious artifacts, and system recovery – following the organization’s incident response plan. Coordinate with IT infrastructure, application owners, and other stakeholders to ensure effective remediation of incidents.</li><li>Proactively hunt for indicators of compromise and hidden threats in logs, network traffic, and endpoint telemetry, even without specific alerts. Use hypothesis-driven techniques and knowledge of attacker TTPs to uncover stealthy or emerging threats that evaded initial detection.</li><li>Continuously tune SIEM/EDR detection rules, thresholds, and SOAR playbooks—automating repetitive response actions to reduce false positives and accelerate containment</li><li>Leverage internal and external threat intelligence sources to enrich analysis and response. Stay updated on new vulnerabilities and adversary tactics; incorporate this knowledge to adjust monitoring rules and incident response strategies. Map observed malicious activities to frameworks like MITRE ATT&amp;CK for reporting and analysis.</li><li>Work closely with global SOC team members and escalate complex incidents to senior analysts or incident response leads when necessary. Collaborate with colleagues in other regions to ensure seamless coverage and knowledge sharing across the security team.</li><li>Document investigation steps, findings, and actions taken for each incident in a clear and concise manner. Prepare incident reports and contribute to post-incident review meetings, highlighting what occurred, how it was resolved, and recommendations to prevent future occurrences.</li><li>Assist in developing and updating incident response playbooks, standard operating procedures, and knowledge base documentation. Provide feedback and suggestions to improve security monitoring tools, analytics content (detection rules), and workflow automation (SOAR playbooks) for greater efficiency and effectiveness.</li><li>Share insights from incidents and trending threats with the broader team to enhance overall awareness. Mentor and guide junior analysts (Tier 1 SOC analysts) by sharing analysis techniques and best practices, elevating the team’s collective skill level.</li></ul> Requirements: <ul><li>Bachelor’s degree in Cybersecurity, Computer Science, Information Systems, or equivalent threat management &amp; incident response experience</li><li>Currently hold cybersecurity certifications such as GCIH, GCFA, GCIA, CEH, others</li><li>With 3 years or more, progressive experience in at least two of the following disciplines:</li><li>Threat Detection &amp; Analysis (leveraging SIEM tools, IDS/IPS, endpoint detection, log analysis, etc.)</li><li>Incident Response &amp; Management (developing response plans, executing playbooks, forensic investigations, root cause analysis)</li><li>Threat Hunting (identifying undetected threats through proactive analysis and hypothesis-driven investigation)</li><li>Cyber Threat Intelligence (gathering and analyzing threat intelligence to inform detection capabilities and preventive measures)</li><li>Network Security (TCP/IP protocols, firewalls, intrusion prevention systems, and network traffic analysis)</li><li>Securing and monitoring operating system and cloud environments (AWS, Azure, GCP), including analyzing cloud service logs and configurations for suspicious activities, and understanding cloud-native security controls and best practices</li><li>Demonstrated ability to:</li><li>Function as a Level 2 or 3 SOC Analyst (analyzing and responding to cybersecurity incidents)</li><li>Preferred Experience:</li><li>Experience with SOAR tools and some proficiency in scripting languages (e.g., Python, PowerShell) to automate repetitive tasks and streamline incident response workflows</li><li>Advanced understanding of emerging threats, zero-day vulnerabilities, and common attack vectors (phishing, malware, ransomware, lateral movement) with the ability to ensure rapid detection and response</li><li>Hands-on experience using SIEM and EDR platforms for centralized log analysis, real-time threat monitoring, and in-depth incident investigations</li><li>In-depth knowledge of the incident response lifecycle</li><li>Proven ability to conduct proactive threat hunting operations, leveraging the MITRE ATT&amp;CK framework to map adversary tactics, techniques, and procedures (TTPs), uncover stealthy threats, and close gaps in detection coverage</li><li>Familiarity with cyber threat intelligence feeds and standards (e.g., STIX, TAXII), incorporating IOCs (Indicators of Compromise) and threat intel data into monitoring and investigations to enrich context and anticipate emerging threats</li><li>Understanding of key security frameworks and regulations (e.g., NIST CSF, ISO 27001, GDPR) and the ability to align threat detection and incident response processes with organizational policies and compliance requirements</li><li>Effective at coordinating with cross-functional teams (IT, DevOps, Business, etc.) during high-impact incidents and translating complex technical findings into clear, actionable insights for executive and non-technical stakeholders</li></ul>

Responsibilities: Software Development: <ul><li>Design, develop, test, and maintain scalable software applications using Java Spring Boot and JavaScript for backend and frontend development, respectively. Build clean, reusable, maintainable, and well-tested code following software engineering best practices.</li></ul> Full Stack Application Development: <ul><li>Develop end-to-end web and mobile applications using Java Spring Boot, React or React Native, backend APIs, database integrations, and modern UI frameworks to deliver intuitive user experiences.</li><li>Design and develop secure RESTful APIs, backend services, authentication mechanisms, and data access layers while ensuring application scalability and performance.</li></ul> AI Enable Engineering: <ul><li>Leverage AI-assisted development tools such as GitHub Copilot, Cursor, ChatGPT, Claude, Amazon Q, or similar tools to improve engineering productivity.</li><li>Experience integrating LLM APIs or AI-powered capabilities into applications is desirable.</li></ul> Collabration: <ul><li>Collaborate with Product Managers, Business Analysts, UX Designers, QA Engineers, Architects, and cross-functional engineering teams to understand business requirements and deliver scalable software solutions.</li><li>Participate in sprint planning, technical discussions, estimation, backlog refinement, and Agile ceremonies.</li></ul> Testing &amp; Quality: <ul><li>Develop unit tests, integration tests, and participate in peer code reviews to ensure software quality, maintainability, reliability, and performance.</li><li>Follow secure coding standards and engineering best practices.</li></ul> Cloud &amp; Devops: <ul><li>Contribute to CI/CD pipelines and cloud-native application deployments using technologies such as Docker, Kubernetes, Azure, AWS, GitHub Actions, or Azure DevOps.</li></ul> Continous Improvement: <ul><li>Identify opportunities to improve software architecture, engineering standards, automation, developer productivity, and application performance.</li><li>Adopt AI-assisted engineering workflows and modern software development practices.</li></ul> Technical Support: <ul><li>Troubleshoot production issues, perform root cause analysis, and resolve application issues while ensuring minimal business disruption.</li></ul> Requirements: <ul><li>Bachelors degree in Computer Science, Engineering, Information Technology, or a related field (or equivalent practical experience).</li><li>3–5 years of professional software development experience.</li><li>Minimum 3+ years of hands-on full-stack development experience.</li><li>Experience developing production-grade web or mobile applications (not academic or personal projects).</li><li>Strong proficiency in Java Spring Boot and JavaScript.</li><li>Experience developing applications using React or React Native.</li><li>Experience developing backend services using Node.js or equivalent backend technologies.</li><li>Strong understanding of REST API development.</li><li>Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or equivalent.</li><li>Strong knowledge of Git and modern software engineering practices.</li><li>Experience working in Agile/Scrum teams.</li><li>Strong understanding of object-oriented programming, software design principles, and data structures.</li></ul>

Responsibilities: <ul><li>Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools.</li><li>Develop and maintain the entire DevOps pipelines.</li><li>Ensure seamless deployment and integration between cloud/prem environments (AWS).</li><li>Integrate AI models into production environments using containerized platforms such as OpenShift.</li><li>Implement and maintain network security protocols to safeguard AI systems and data pipelines.</li><li>Collaborate with cross-functional teams to understand AI workflows and translate them into robust engineering solutions.</li><li>Monitor and optimize system performance, reliability, and scalability.</li><li>Support CI/CD processes and infrastructure for AI model deployment and updates.</li></ul> Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related field.</li><li>Bash and Unix/Linux command-line toolkit is a must-have.</li><li>Deep technical background, with hands-on experience in supporting CI/CD pipelines (Bitbucket, Jenkins, Artifactory, Sonar, Veracode for SAST, JIRA workflow, and Confluence).</li><li>Hands-on experience with OpenShift, Docker, Kubernetes.</li><li>Knowledge of cloud platforms (e.g. AWS) is a must-have.</li><li>Exposure to data and network security and compliance in AI systems.</li><li>Knowledge of API integration and microservices architecture.</li><li>Proficiency in Python used both for automation and ML-related tasks</li><li>Knowledge of Workflow Orchestrator, such as Ctrl-M</li><li>Good knowledge of Logging and Monitoring tools, such as Splunk and Geneos.</li><li>Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, Open Telemetry.</li><li>Understanding of Generative AI (e.g. prompt engineering, RAG pipelines) and Agentic AI concepts.</li></ul>

Responsibilities: People, Talent and Cross-Functional Collaboration:&nbsp; <ul><li>Ensure optimal staffing levels across front-end, back-end, full-stack, and platform specializations.&nbsp;</li><li>Hire, coach, and develop top-tier engineering talent.</li><li>Manage direct reports and technical leads, address performance issues promptly, and build strong relationships with Product, Design, Platform, Data, and agile train leadership to deliver cohesive, customer-focused solutions.</li><li>Community of Practice, Developer Experience and AI-Driven Engineering: As AI tooling becomes inseparable from modern engineering practice, own the convergence of Community of Practice standards and AI adoption as a single discipline.&nbsp;</li><li>Foster best practice adoption across the engineering community with AI tooling treated as a first-class part of the practice.</li><li>Define standards for responsible AI adoption — including when to use AI coding assistants, agents, skills, and MCP integrations versus traditional approaches.</li><li>Establish clear guidance on the distinction between AI Skills (deterministic capabilities) and Agents (autonomous, multi-step workflows). </li><li>Evaluate, pilot, and roll out AI tools (GitHub Copilot, Claude Code, Cursor, Windsurf, Continue.dev, Aider, Cline, Ollama). </li><li>Define governance for AI use in regulated financial services contexts including data handling, PII protection, IP compliance, and code provenance. </li><li>Track and measure the combined impact of CoP practices and AI adoption on cycle time, PR throughput, defect rates, and developer satisfaction.</li><li>System Architecture and Technical Direction: Own a modern view of system architecture spanning client, server, data, integration, and AI layers.&nbsp;</li><li>Champion patterns such as micro-frontends, BFF, event-driven, API-first, serverless, and composable architectures.&nbsp;</li><li>Partner with Enterprise Architects on platform alignment.&nbsp;</li><li>Guide trade-off decisions (monolith vs. microservices, sync vs. async, build vs. buy). Use AI-powered architecture tools to accelerate design exploration and generate ADRs.</li><li>Ensure teams document decisions so both humans and AI agents can reason about the system. </li><li>Understand how AI tools interact with system architecture — including RAG, vector databases, MCP integrations, and agentic workflows.</li></ul> Strategic Planning, Delivery and Operational Excellence:&nbsp; <ul><li>Ensure plans align with CoP goals, review quarterly commitments to flag risks early, and step in to resolve conflicts between product, design, and engineering.&nbsp;</li><li>Drive CI/CD best practices, ensure high-quality scalable solutions across the stack, and provide on-call support during escalations.&nbsp;</li><li>Support tech leads hands-on when needed, regardless of which layer of the stack the problem lives in.</li></ul> Requirements: <ul><li>Strong hands-on background in modern front-end technologies (ReactJS, TypeScript, NextJS, Cypress) as an anchor foundation, with working knowledge of back-end technologies, APIs, microservices, and data layer concepts.&nbsp;</li><li>Experience with AWS cloud services, CI/CD pipelines, and modern DevOps practices.&nbsp;</li><li>Proven ability to lead engineers working across the full stack.</li><li>Solid grounding in system architecture fundamentals — distributed systems, scalability, CAP trade-offs, caching, messaging, API design — and familiarity with modern patterns (micro-frontends, BFF, event-driven, CQRS, serverless, composable architectures).&nbsp;</li><li>Experience making and documenting architecture decisions (ADRs), with understanding of how AI-native architecture (RAG pipelines, vector databases, agent orchestration) differs from traditional architecture.</li><li>Hands-on experience with AI coding assistants (GitHub Copilot, Claude Code, Cursor, or equivalent) with clear understanding of the difference between AI Skills and Agents, familiarity with MCP (Model Context Protocol), RAG patterns, and experience defining AI usage guidelines and governance frameworks for regulated environments.&nbsp;</li><li>Awareness of the open-source AI tooling ecosystem (Continue.dev, Aider, Cline, Ollama).</li><li>Proven experience leading and growing high-performing engineering teams, running or contributing to a Community of Practice, and strong communication skills with the ability to influence across organizational levels.</li></ul>

Role Description: <ul><li>We are seeking an experienced Lead Quality Automation Engineer to join our growing Quality Engineering practice in Leeds.&nbsp;</li><li>This role is suited to a highly technical Quality Engineer who enjoys solving complex engineering challenges while working directly with clients across multiple industries.&nbsp;</li><li>You will play a key role in designing automation solutions, driving engineering best practices, mentoring team members, and helping organisations modernise their quality engineering capabilities.&nbsp;</li><li>As a Lead Quality Automation Engineer, you will remain hands-on with automation development while providing technical leadership across delivery teams.&nbsp;</li></ul> Responsibilities:&nbsp; <ul><li>Design, develop and maintain scalable automated testing frameworks for enterprise applications.&nbsp;&nbsp;</li><li>Deliver high-quality automation solutions using modern testing tools and object-oriented programming languages.&nbsp;&nbsp;</li><li>Work collaboratively with software engineers, architects, product owners, and business stakeholders throughout the software development lifecycle.&nbsp;&nbsp;</li><li>Champion Shift-Left Quality Engineering practices by embedding testing early in the development process.&nbsp;&nbsp;</li><li>Analyse application source code to identify defects, improve test coverage, and support overall software quality.&nbsp;&nbsp;</li><li>Contribute to Continuous Integration and Continuous Delivery (CI/CD) pipelines to enable efficient automated testing.&nbsp;&nbsp;</li><li>Apply AI-assisted engineering tools and Generative AI technologies to improve testing efficiency and engineering productivity.&nbsp;&nbsp;</li><li>Provide technical leadership, mentoring, and guidance to junior engineers and project teams.&nbsp;&nbsp;</li><li>Support clients in adopting modern Quality Engineering practices and continuous improvement initiatives.&nbsp;&nbsp;</li><li>Participate in technical discussions, solution design, and engineering governance activities.&nbsp;&nbsp;</li></ul> Requirements: <ul><li>Proven experience in Quality Engineering and Test Automation within enterprise environments.&nbsp;&nbsp;</li><li>Hands-on experience developing and maintaining automation frameworks.&nbsp;&nbsp;</li><li>Strong programming experience in one or more object-oriented languages such as Java, Python, C#, JavaScript, or TypeScript.&nbsp;&nbsp;</li><li>Experience with modern automation frameworks such as Playwright, Selenium, or equivalent.&nbsp;&nbsp;</li><li>Experience working with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform.&nbsp;&nbsp;</li><li>Good understanding of Continuous Integration and Continuous Delivery (CI/CD) principles.&nbsp;&nbsp;</li><li>Experience working with AI productivity tools such as GitHub Copilot, Claude, or similar technologies.&nbsp;&nbsp;</li><li>Strong understanding of software development lifecycle (SDLC) and Shift-Left Testing methodologies.&nbsp;&nbsp;</li><li>Excellent communication and stakeholder management skills with the ability to work directly with clients.&nbsp;&nbsp;</li><li>Demonstrated ability to work independently while managing multiple priorities.&nbsp;&nbsp;</li></ul> Preferred Qualifications&nbsp; <ul><li>Commercial experience implementing Generative AI solutions within Quality Engineering.&nbsp;&nbsp;</li><li>Experience working within consulting or professional services organisations.&nbsp;&nbsp;</li><li>Knowledge of Agentic AI concepts.&nbsp;&nbsp;</li><li>Familiarity with LangChain and LangGraph.&nbsp;&nbsp;</li><li>Experience mentoring engineers and providing technical leadership.&nbsp;&nbsp;</li><li>Exposure to both public and private sector projects.&nbsp;&nbsp;</li></ul> Personal Attributes&nbsp; The successful candidate will demonstrate:&nbsp; <ul><li>Strong analytical and problem-solving skills.&nbsp;&nbsp;</li><li>Excellent verbal and written communication abilities.&nbsp;&nbsp;</li><li>Adaptability in fast-paced consulting environments.&nbsp;&nbsp;</li><li>A continuous learning mindset with evidence of ongoing professional development.&nbsp;&nbsp;</li><li>A collaborative approach with the ability to influence technical and non-technical stakeholders.&nbsp;&nbsp;</li></ul> Working Arrangement&nbsp; <ul><li>This role follows a hybrid working model with an expectation of approximately two to three days per week onsite, depending on client requirements.&nbsp;</li><li>Some travel to client locations may be required.&nbsp;</li></ul> Security Requirements&nbsp; <ul><li>Candidates must either hold Security Clearance (SC) or be eligible to obtain SC Clearance in accordance with UK Government requirements.&nbsp;</li></ul>

Responsibilities: <ul><li>Data Analysis: Collects, transforms, and analyzes data from multiple sources to identify trends, patterns, anomalies, and actionable insights that support reporting, performance tracking, and decision making.</li><li>Reporting &amp; Visualization: Implements detailed reports and dashboards using various tools, designs and completes data visualizations to communicate moderately complex data clearly.</li><li>Data Modeling &amp; Automation: Supports data models, reporting logic, and workflow automation, while identifying and implementing opportunities to improve data collection and reporting processes using standard data management and reporting practices.</li><li>Advanced Analytics Awareness: Familiarity with predictive analytics, AI/ML, and data science concepts to support evolving analytics solutions.</li><li>Data Quality &amp; Requirement Support: Validates data, supports reporting requirements, and helps ensure the accuracy and consistency of analytics solutions.</li></ul> Requirements: <ul><li>Bachelor’s degree in a related field such as Data Science, Statistics, Computer Science, Business Analytics, or a related discipline, or equivalent practical experience.&nbsp;</li><li>Minimum of 3-4 years of relevant work experience in data analytics, reporting, or business intelligence roles.</li><li>Strong skills in analyzing data and translating reporting needs into effective analytics solutions and insights.</li><li>Very strong skills in Power BI and data visualization.</li><li>Proficiency in SQL, Excel, Power Query, and related tools such as VBA or Python for analysis, modelling, and visualization.</li><li>Working knowledge of data warehousing, data lakes, and cloud data platforms such as Snowflake or AWS.</li><li>Experience automating workflows and building low-code solutions using Power Platform tools such as Power Automate and Power Apps.</li><li>Familiarity with (predictive) analytics, AI/ML and data science.</li><li>Business understanding and financial acumen to interpret data and generate practical insights.</li><li>Comfortable working in agile ways of working, managing multiple priorities, and contributing effectively both independently and in a team environment.</li></ul>

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31 aws Jobs found

AI Analytics and Visualization Engineer

Application Performance Monitoring Lead Specialist VP2

AVP, Principal Software Engineer (Senior Technical lead)

Enterprise Analytics (AI) – TDM - Transformation Lead

Senior Analyst, Threat Detection and Response

Software Engineer – Ag & Trade

Enterprise Analytics – Machine Learning Ops/AI Projects (VP1)

VP, Engineering Manager

Lead Quality Automation Engineer

Consultant, Data Analytics & Reporting-Food

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AI Analytics and Visualization Engineer

Application Performance Monitoring Lead Specialist VP2

AVP, Principal Software Engineer (Senior Technical lead)

Enterprise Analytics (AI) – TDM - Transformation Lead

Senior Analyst, Threat Detection and Response

Software Engineer – Ag & Trade

Enterprise Analytics – Machine Learning Ops/AI Projects (VP1)

VP, Engineering Manager

Lead Quality Automation Engineer

Consultant, Data Analytics & Reporting-Food

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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WhiteCrow is on a mission to connect companies with the best talent across the globe.