Technical Trainer - Data Engineering & AI

About the role

FDM is looking for an experienced Data Engineer who is passionate about developing people and helping others build successful technology careers. The role moves beyond project delivery: you will design practical learning experiences, mentor aspiring consultants and help build the technical capabilities clients need across data, cloud, analytics and AI. You will bring real-world expertise into FDM's Skills Lab, turning complex technical concepts into hands-on learning.

Key responsibilities

• Deliver engaging training on modern data engineering concepts and technologies
• Design practical labs, projects and technical exercises that reflect real client environments
• Develop consultants' skills in Python, SQL, data modelling and data pipelines
• Mentor consultants and give constructive feedback to accelerate their development
• Bring current industry practices and trends into training programmes
• Contribute to curriculum design and continuously improve learning content
• Help consultants understand how data platforms support analytics, machine learning and AI workloads
• Partner with fellow instructors and subject matter experts to strengthen FDM's Data & Analytics capabilities
• Ensure training aligns with evolving client demand and market trends

Required profile

• Experienced data professional who enjoys sharing knowledge and helping others grow
• Able to explain technical concepts clearly and bring industry experience to life through practical examples
• Currently working as a Data Engineer, Senior Data Engineer, Analytics Engineer, Data Platform Engineer, Data Engineering Lead, Technical Trainer, Technical Instructor or Learning Consultant (Technology)
• Excellent communication and stakeholder management skills
• Passion for coaching, mentoring, teaching or knowledge sharing

Required skills

• Strong Python and SQL skills
• Experience building, maintaining or supporting data pipelines and data platforms
• Understanding of modern data engineering principles and scalable data architectures
• Experience with cloud platforms such as AWS, Azure or Google Cloud
• Knowledge of data quality, governance and best practices
• Desirable: Apache Spark, Kafka, Hadoop or Hive; data warehousing and ETL; Snowflake or other cloud data platforms; batch and real-time data processing; analytics and ML data preparation; curriculum development, technical training or mentoring programmes