Corndel

• Manage a caseload of learners, building trusted relationships through high quality coaching, mentoring, and structured teaching. • Deliver engaging one to one sessions and workshops that make data concepts accessible, relevant, and practical. • Empower learners to develop confidence with data by encouraging curiosity, critical thinking, and reflection. • Create an inclusive, psychologically safe learning environment where learners feel comfortable asking questions, testing ideas, and learning from mistakes. • Support learners to develop core data skills, including data preparation, analysis, visualisation, and interpretation. • Guide learners through programme milestones, assessments, and portfolio development, ensuring consistent progress and timely completion. • Work collaboratively with colleagues across Operations, Product, and Curriculum to deliver a consistent and high quality learner experience.

• Coach and mentor learners through 1‑to‑1 sessions and workshops • Support learners to build low‑code and no‑code automations using Microsoft Power Platform • Demonstrate best practice in workflow design, testing, documentation, and ethical AI use • Troubleshoot and guide learners on real business automation challenges • Support portfolio development and End Point Assessment readiness

• Coach and mentor a caseload of Level 6 AI Engineering apprentices • Deliver engaging 1:1 coaching, workshops, and group learning • Support learners across the full machine learning lifecycle, from problem scoping to deployment and monitoring • Guide learners through End Point Assessment (EPA) and portfolio development • Promote responsible AI, ethics, security, and governance • Collaborate with employers and internal teams to ensure high‑quality learner outcomes

• Coach and mentor a caseload of learners through 1:1 sessions and workshops • Teach practical data engineering concepts in a way that’s clear, relevant, and grounded in real‑world experience • Help learners design and build reliable, scalable, secure data solutions - not just working code • Guide learners through assessments and portfolios with high standards and supportive feedback • Model strong professional judgement around performance, cost, security, privacy, and ethics

• Manage a caseload of learners, building trusted relationships • Deliver engaging one-to-one sessions and workshops • Empower learners to think critically about problems • Support learners to apply core business analysis practices • Coach learners on how AI can be used to improve workflows

• Coach, mentor, and teach learners on Corndel’s Level 4 Data Analyst programme. • Deliver engaging one to one sessions and workshops that make analytical concepts accessible, relevant, and practical. • Empower learners to think critically about data, challenge assumptions, and reflect on the implications of their analysis. • Create an inclusive, psychologically safe learning environment where learners feel confident asking questions, testing ideas, and learning from mistakes. • Support learners to develop core analytical skills, including data preparation, querying, analysis, modelling, and visualisation. • Coach learners to use tools such as Excel, Power BI, SQL, Python, and related platforms to generate meaningful insights. • Guide learners through programme milestones, assessments, and portfolio development, ensuring consistent progress and timely completion. • Work collaboratively with colleagues across Operations, Product, and Curriculum to deliver a consistent and high-quality learner experience.

• Manage a caseload of learners, building trusted relationships through structured one‑to‑one coaching and group workshops. • Support learners at different stages of confidence and digital maturity, adapting your approach to meet individual needs. • Create an inclusive, psychologically safe learning environment where learners feel comfortable asking questions, practising new skills, and learning from mistakes. • Encourage learners to take ownership of their development, building confidence through practical application and reflection. • Coach learners to use Microsoft 365 tools (including Outlook, Teams, SharePoint, Word, Excel and PowerPoint) to improve everyday productivity. • Guide learners in the practical use of Microsoft Copilot and other AI tools, including prompt-based approaches that enhance clarity, efficiency and decision making. • Support learners to develop safe, ethical, and responsible AI habits, including awareness of data privacy, bias, and security considerations. • Help learners recognise opportunities to apply AI enabled workflows in real workplace tasks, balancing innovation with good professional judgement. • Support learners to develop foundational digital support skills, such as diagnosing simple application issues, providing user support, and troubleshooting. • Guide learners through programme milestones, assessments, and portfolio evidence, ensuring consistent progress and timely completion.

• Coach and mentor a caseload of learners through 1:1 sessions and workshops • Teach practical data engineering concepts in a way that’s clear, relevant, and grounded in real‑world experience • Help learners design and build reliable, scalable, secure data solutions - not just working code • Guide learners through assessments and portfolios with high standards and supportive feedback • Model strong professional judgement around performance, cost, security, privacy, and ethics

• Manage a caseload of learners, building trusted relationships through structured one‑to‑one coaching and group workshops • Support learners at different stages of confidence and digital maturity, adapting your approach to meet individual needs • Create an inclusive, psychologically safe learning environment where learners feel comfortable asking questions, practising new skills, and learning from mistakes • Encourage learners to take ownership of their development, building confidence through practical application and reflection • Coach learners to use Microsoft 365 tools to improve everyday productivity • Guide learners in the practical use of Microsoft Copilot and other AI tools • Support learners to develop safe, ethical, and responsible AI habits • Help learners recognise opportunities to apply AI enabled workflows in real workplace tasks • Support learners to develop foundational digital support skills, such as diagnosing simple application issues, providing user support, and troubleshooting • Progress, Quality & Outcomes: Guide learners through programme milestones, assessments, and portfolio evidence • Collaborate with colleagues across Operations, Product, and Curriculum to deliver a consistent and high-quality learner experience

• Manage a caseload of learners with high-quality coaching, mentoring, and teaching • Deliver engaging one-to-one sessions and workshops to make data concepts accessible and practical • Support learners in developing core data skills, data analysis, and using data tools • Guide learners through programme milestones, ensuring progress and compliance • Collaborate with colleagues to enhance learner experiences and outcomes