Senior Trainer – Data Engineering (Advanced + AI Integration)

Revature • Chicago, IL

3d

About The Position

We are looking for a Senior Trainer - Data Engineering with strong expertise in modern data platforms and AI-driven data systems. The ideal candidate will be an experienced data engineer capable of delivering advanced training on end-to-end data engineering workflows - from data ingestion and transformation to preparing high-quality datasets for AI and machine learning applications. This role is central to training the next generation of Data Engineers and AI-ready professionals, leveraging cutting-edge tools such as Databricks, Apache Spark, Kafka, Airflow, Delta Lake, and Snowflake.

Requirements

• 5+ years in Data Engineering , Big Data , or AI/ML Infrastructure Development
• Strong programming skills in Python (pandas & numpy) and SQL
• Hands-on experience with Databricks , Apache Spark , and PySpark
• Deep understanding of data lakes , Delta Lake , and lakehouse architecture
• Proficiency with streaming frameworks such as Kafka or Kinesis
• Experience with Airflow or other orchestration tools.
• Familiarity with MLflow , TensorFlow , or PyTorch for data-to-AI workflows.
• Cloud expertise in AWS (Glue, Redshift, Sagemaker) , Azure (Data Factory, Synapse, ML Studio) , or GCP (Dataflow, Vertex AI, BigQuery)
• Bachelor’s or Master’s in Computer Science, Data Science, or related technical discipline.
• Excellent communication, presentation, and mentoring skills.
• Prior experience as a corporate trainer, instructor, or mentor in a data/AI-focused program is preferred.
• Ready to deliver on-site and virtual training

Nice To Haves

• Certifications such as: Databricks Certified Data Engineer or Machine Learning Professional AWS Certified Machine Learning – Specialty Google Professional Data Engineer / ML Engineer
• Familiarity with AI model lifecycle management , feature stores , and MLOps best practices
• Demonstrated ability to bridge data engineering and AI/ML domains
• Passion for teaching, mentoring, and simplifying complex, end-to-end data and AI systems.

Responsibilities

• Deliver in-depth, interactive, and hands-on sessions on advanced data engineering and AI integration
• Train and mentor learners on: Distributed processing using Apache Spark and Databricks.
• Data orchestration with Airflow and CI/CD pipelines for data workflows Real-time streaming using Kafka and Kinesis Lakehouse architectures using Delta Lake , Snowflake , and cloud-native solutions Data preparation for AI/ML pipelines , including feature engineering and dataset versioning Working with MLflow , Databricks AutoML , and AI/ML integrations on cloud platforms Implementing data governance, lineage, and monitoring best practices
• Guide learners through AI-ready data engineering projects , combining data pipelines with model development and deployment.
• Collaborate with curriculum designers to integrate emerging AI and data science tools (e.g., Vector Databases, MLOps frameworks) into the training modules.
• Conduct performance evaluations, code reviews, and one-on-one learner mentoring sessions.
• Stay current with AI trends , modern data infrastructure , and cloud-native innovations to continuously enrich the training experience.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior