Senior Trainer – Data Engineering, Advanced, AI Integration

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🕒 February 16

🌽 Illinois, New Jersey, +2 more states – Remote

🌽 Illinois – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🤠 Texas – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Revature

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

💰 Series A on 2016-03

Revature is a tech engineering services provider with a focus on talent enablement and talent transformation in both bespoke services and enterprise applications. The company works with Fortune 500 companies, government organizations, and top systems integrators to grow their business by providing highly trained Software Engineering teams.

📋 Description

• 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 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.

🎯 Requirements

• Minimum 4-5 years of professional experience in Data Engineering, Big Data, or related domains. • 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.

🏖️ Benefits

• Health insurance • Professional development