One of our MNC Client is Hiring Data Engineer Trainer As a Trainer, you will Teach production-grade Data Engineering and Handle mixed learner depth - Break concepts down for freshers while retaining credibility with experienced engineers. Develop practitioners who can think, troubleshoot, explain and make sound engineering judgments.

Key Responsibilities: Curriculum &

• Content Development Architect end‑to‑end training curriculam: slide decks, guided notebooks, quizzes, hands‑on labs, and capstone projects Balance theory and practice with a 50/50 lecture‑to‑lab ratio Update materials iteratively based on learner feedback and platform enhancements Training Delivery Lead engaging virtual and in‑person sessions, live demos, and whiteboard discussions Facilitate self‑paced e‑learning modules and mentor learners through code reviews and project assessments Measure effectiveness via surveys, hands‑on evaluations, and grading rubrics Technical Enablement Teach core Databricks componentsApache Spark, Delta Lake, MLflow, Unity Catalog, Databricks SQL, Delta Live Tables, and Workflows Guide learners through real‑world use cases: batch & streaming ETL, ML pipelines, data governance, and performance tuning Project Coaching &

• Support Mentor capstone teams on end‑to‑end implementations, from data ingestion through model deployment Troubleshoot learner environments and provide “office‑hours” support Continuous Improvement &

• Thought Leadership Stay current on Databricks product roadmap and industry best practices Contribute to internal playbooks, cookbook recipes, and knowledge‑share sessions Required Skills &

Experience Instructional Design &

• Facilitation 2+ years delivering technical training (virtual and classroom)



with robust adult‑learning methodology Skilled at creating interactive labs, assessments, and capstone challenges Databricks Lakehouse Expertise Deep proficiency in Apache Spark (PySpark RDD/DataFrame/Dataset) and Delta Lake (ACID, time travel, Z‑ordering) Solid experience with MLflow (experiment tracking & model registry), Unity Catalog, Databricks SQL, and Photon performance tuning Programming &

• Data Engineering Advanced Python (UDFs, pandas/NumPy) and SQL (window functions, query optimization) Practical knowledge of Scala for Spark application tuning (optional but advantageous) Hands‑on with batch (Auto Loader, COPY INTO) and streaming (Structured Streaming, watermarking) ETL patterns, following Medallion architecture Machine Learning Foundations: Feature engineering, hyperparameter tuning, model packaging/deployment Exposure to advanced analytics (NLP, recommendation systems, real‑time inference) Cloud &

• DevOps: Experience provisioning and securing Databricks on AWS, Azure, or GCP (Terraform/ARM templates) Building CI/CD pipelines for notebook version control, workflow deployment, and model lifecycles Data Governance &

• Security: Designing Unity Catalog hierarchies, enforcing row/column‑level security, and managing audit logging Familiarity with GDPR/HIPAA compliance and encryption/key‑management best practices Consulting &

• Stakeholder Management: Client‑facing experience in pre‑sales or solutions architecture, aligning training to real business challenges Agile mindset: sprint planning, iterative demos, and feedback loops Preferred Qualifications Certifications Databricks Certified Data Engineer Associate or ML Associate (required) Cloud certifications (AWS Big Data Specialty, Azure Data Engineer, or GCP Professional Data Engineer)

📌 Lead Data Engineering Educator (Chennai)
🏢 BL Consultants
📍 Chennai