Level 7 Data & AI Tutor

Projecting Success
UK
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Compensation
£55,000.0 - £70,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Artificial Neural Networks Microsoft Azure Big Data Cloud Computing Information Engineering Data Systems Database Storage Structures Python (Programming Language) Machine Learning Natural Language Processing
+12 more
NumPy Software Tools Tensorflow SciPy SQL Databases Reinforcement Learning Apache Spark Deep Learning Pandas Scikit Learn Data Management Data Pipelines

Job description

As a Level 7 Data Engineer Tutor, you will play a pivotal role in developing the next generation of skilled data professionals. Your expertise will empower learners to master complex data engineering concepts, tools, and technologies while ensuring they meet the highest industry standards.

We are seeking a passionate tutor with deep technical knowledge and hands-on experience in data engineering. Your role will involve teaching, coaching, and mentoring learners across our range of apprenticeship programs, including:

· Level 4 Data Analyst

· Level 7 AI (Artificial Intelligence) Specialist

You will also provide guidance in the latest data engineering tools, platforms, and frameworks, ensuring learners develop practical, job-ready skills., Teaching, Learning & Assessment

· Deliver structured, engaging, and practical training sessions on applied machine learning, aligned with Level 7 apprenticeship standards.

· Teach topics such as neural networks, deep learning, NLP, data pipelines, big data frameworks, cloud computing, and database management.

· Provide hands-on training with tools like SQL, Python, Spark, and some cloud platforms (AWS, Azure).

· Offer constructive feedback on assignments, projects, and assessments to support learner progression.

· Ensure compliance with Safeguarding, PREVENT, and EDI policies.

Learner Management & Support

· Manage a caseload of learners, offering tailored coaching, mentoring, and support.

· Identify additional learning needs and provide appropriate interventions.

· Prepare learners for End-Point Assessments (EPA), ensuring they understand competency requirements.

· Support learners with academic writing and dissertation development.

Progress Monitoring & Compliance

· Track and monitor learner progress through regular reviews and assessments.

· Ensure learners meet Off-The-Job (OTJ) training requirements and maintain accurate records.

· Adhere to apprenticeship standards and funding regulations, ensuring compliance with EPAOs, ESFA, and awarding body requirements.

Employer Engagement & Collaboration

· Work closely with employers to align training with real-world data engineering needs.

· Conduct employer meetings to discuss learner progress and ensure alignment with business objectives.

Internal Collaboration & Quality Assurance

· Contribute to curriculum development, standardization, and quality improvement initiatives.

· Participate in peer observations, audits, and professional development activities to maintain high teaching standards.

· Engage with internal teams to ensure accurate learner records and compliance with policies.

Staying Current in Data Engineering & AI

· Stay updated with emerging technologies in data engineering, cloud computing, and AI.

· Incorporate industry trends and best practices into teaching methodologies.

· Share knowledge with colleagues to enhance teaching and learning strategies.

Data Management & Reporting

· Maintain accurate records in the Learner Management System (LMS).

· Ensure timely and accurate reporting of learner progress, withdrawals, and compliance data.

· Ensure adherence to ISO and Cyber Essentials standards.

Problem Solving & Continuous Improvement

· Identify and resolve learner or employer concerns proactively.

· Implement interventions to support at-risk learners and reduce withdrawals.

· Provide feedback to enhance program delivery and learner experience.

Requirements

Do you have experience in Teaching?, Do you have a Bachelor’s degree?, We are looking for an individual who is:

· Technically proficient - Expertise in data engineering principles, cloud platforms, and modern data technologies. Comfortable with a wide range of machine learning approaches (supervised, unsupervised and reinforcement learning)

· Strong Python Skills - Familiar with development in Python and using common data/machine learning packages (NumPy, Pandas, SKLearn, SciPy, Tensorflow etc)

· Passionate about teaching - Enthusiastic about mentoring and supporting learners in achieving success.

· Industry-aware - Up to date with the latest data engineering and AI advancements.

· Highly organized - Able to manage multiple learners and maintain high-quality teaching standards.

· Driven and proactive - Takes ownership of learner success and continuously seeks to improve teaching methods.

· An excellent communicator - Capable of explaining complex technical concepts to diverse learners with varying levels of experience., Desirable:

· Assessor qualification (e.g., TAQA, A1, D32/D33).

· PCGE, CertEd or other recognised Level 5 or above Teaching Qualification.

· Experience delivering Level 4 and Level 7 Data Engineer and AI apprenticeships.

Essential:

· Strong background in data engineering, with expertise in machine learning technologies, Python development, data pipelines, and database structures (relational and non-relational).

· Hands-on experience with SQL, Python, and some cloud computing (AWS, Azure).

· Understanding of apprenticeship standards, assessment practices, and regulatory requirements.

· Excellent communication skills - ability to engage learners and simplify complex concepts.

· Ability to work independently and manage multiple tasks effectively.

· Commitment to continuous professional development.

· Knowledge of Educational Inspection Framework and OFSTED expectations.

Benefits & conditions

Pulled from the full job description

  • Flexitime
  • Annual leave
  • Company pension
  • Work from home

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