Senior Trainer – Data Engineering; Advanced + AI Integration

Position Summary

Senior Trainer – Data Engineering – Capable of delivering advanced training on end‑to‑end data engineering workflows from ingestion to AI‑ready data sets, teaching modern data platforms (Databricks, Apache Spark, Kafka, Airflow, Delta Lake, Snowflake). The role trains the next generation of Data Engineers and AI‑ready professionals.

• 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.
• Guide data orchestration with Airflow and CI/CD pipelines for data workflows.
• Teach real‑time streaming using Kafka or Kinesis and lakehouse architectures with Delta Lake, Snowflake, and cloud‑native solutions.
• Prepare datasets for AI/ML pipelines, including feature engineering and dataset versioning.
• Work with MLflow, Databricks AutoML, and AI/ML integrations on cloud platforms.
• Implement 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 (vector databases, MLOps frameworks) into training modules.
• Conduct performance evaluations, code reviews, and one‑on‑one learner mentoring sessions.
• Keep current with AI trends, modern data infrastructure, and cloud‑native innovations to continuously enrich training.

• 5+ years of professional experience 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, Tensor Flow, or PyTorch for data‑to‑AI workflows.
• Cloud expertise in at least one major provider (AWS, Azure, or GCP) and its data services.
• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical discipline.
• Excellent communication, presentation, and mentoring skills.
• Prior experience as a corporate trainer, instructor, or mentor in a data/AI‑focused program.
• Availability to deliver on‑site and virtual training.

• Certifications such as Databricks Certified Data Engineer, 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.

Revature is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, genetic information, age, marital status, protected veteran status, or disability status.