IT Trainer - Data Engineering

We are looking for a passionate and experienced Data Engineer Trainer to design, develop, and deliver high-quality learning content in Data Engineering and Modern Data Platforms. The ideal candidate should possess strong technical expertise in Python, SQL, NoSQL databases, Big Data technologies, Cloud Data Engineering, Data Warehousing, Data Lakes, ETL/ELT processes, and modern data transformation tools.

The Trainer will be responsible for curriculum development, content creation, instructor-led training, hands-on lab development, assessment design, and supporting academic institutions and corporate learning initiatives. The role requires excellent communication skills, strong industry knowledge, and a passion for mentoring engineering students and working professionals.

Key Responsibilities

• Design and develop industry-aligned curriculum and learning paths in Data Engineering.
• Create engaging training materials including presentations, lab manuals, coding exercises, assignments, case studies, and projects.
• Deliver instructor-led classroom and virtual training sessions.
• Mentor students during hands-on labs, capstone projects, and hackathons.
• Develop practical assessments, coding challenges, and evaluation rubrics.
• Review and continuously enhance existing learning content based on industry trends.
• Collaborate with instructional designers and academic partners to improve learner outcomes.
• Provide technical guidance to trainers and support faculty enablement programs.
• Design and develop real-world projects on ETL, Data Lakes, Data Warehouses, Big Data, and Cloud Data Engineering.
• Stay updated with emerging Data Engineering technologies and integrate them into the curriculum.

Required Technical Skills

Programming & Databases

• Python Programming for Data Management, OOPS
• Advanced SQL
• NoSQL Databases (MongoDB, Cassandra, DynamoDB)

Data Engineering

• ETL/ELT Development and Data Integration
• Data Pipeline Design and Optimization
• Data Warehousing and Dimensional Modeling
• Data Lake and Lakehouse Architectures

Big Data Technologies

• Hadoop Ecosystem
• Apache Spark / PySpark
• Kafka and Distributed Data Processing

Data Engineering Tools

• Databricks
• Snowflake
• Apache Airflow
• Data Transformation and Orchestration Tools

Cloud Data Platforms

• Azure Data Factory, Azure Databricks, Synapse Analytics
• AWS Glue, EMR, Redshift
• GCP BigQuery, Dataflow, Dataproc

Preferred Skills

• Docker and Kubernetes
• Git and GitHub
• REST APIs
• DataOps and CI/CD Concepts
• Power BI or Tableau
• Delta Lake and Apache Iceberg
• Data Governance and Data Quality Concepts

Educational Qualification

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, Data Science, or a related field.
• Candidates with a Bachelor of Engineering (B.E./B.Tech.), Master of Engineering(M.E./M.Tech), equivalent qualifications are encouraged to apply.

Preferred Experience

• Experience in EdTech, higher education, or corporate training.
• Experience delivering Data Engineering training to engineering students or working professionals.
• Experience creating project-based learning content and technical assessments.
• Hands-on industry experience as a Data Engineer, Big Data Engineer, Cloud Data Engineer, or Data Platform Engineer.
• Experience with Databricks, Snowflake, and Cloud Data Engineering services.
• Experience with Learning Management Systems (LMS) is an added advantage.

Key Deliverables

• Curriculum and syllabus design for Data Engineering programs
• Instructor presentations
• Lab manuals and coding exercises
• Assignments and assessments
• Capstone projects
• Question banks and evaluation rubrics
• Faculty enablement sessions
• Student mentoring and technical support