Tech Trainer

• Experience Requirement: 612 Years
  
• Employment Type: Full-Time
  

• Classroom Instruction & Learning Delivery
  

• Technical Lecture & Lab Facilitation: Lead advanced hands-on instructional cohorts for heterogeneous batches adapting delivery formats seamlessly for fresh engineering graduates up to seasoned IT professionals.
  
• Databricks & Lakehouse Architectures: Deliver deep-dive training on Apache Spark PySpark Databricks Workspaces Delta Lake and Unity Catalog. Teach cohorts how to build scalable optimized batch and streaming data pipelines within a lakehouse framework.
  
• Cloud Data Architecture: Instruct on end-to-end data pipelines using Microsoft Azure (Data Factory Synapse Analytics) Google Cloud Platform (BigQuery Compute Engine GKE) and AWS foundational data services.
  
• Data Warehousing & ETL Frameworks: Deliver comprehensive curricula on modern cloud data warehouses like Snowflake alongside legacy ETL middleware systems such as Informatica PowerCenter.
  
• RDBMS & Production DBA Operations: Teach deep-dive database concepts across Oracle (11g/12c/19c) Microsoft SQL Server MySQL and PostgreSQL. Provide training on performance tuning SQL/PL-SQL execution structures (stored procedures packages triggers) RMAN backup/recovery and Automatic Storage Management (ASM).
  
• Data Operations & Automation: Train cohorts on core operational automation workflows including Unix/Linux basics shell scripting job scheduling mechanisms logging error handling and incident reporting tools (e.g. ServiceNow).
  

• Curriculum Architecture & Content Creation
  

• Build evaluate and maintain rigorous technical syllabi instructional decks and sandbox lab architectures modeled after industry standards and certification metrics (such as Databricks Certified Data Engineer Associate/Professional Azure DP-203 and Oracle Certified Associate paths).
  
• Translate real-world application frameworks (e.g. multi-tier system architectures real-time streaming data or legacy database migrations) into clear digestible project-based training modules.
  

• Performance Management & Training Governance
  

• Measure grade and monitor cohort technical performance using metrics-based scorecards to ensure training programs translate directly into client-project and production readiness.
  
• Coordinate closely with delivery managers and corporate stakeholders to map specific technical skill gaps and continuously adapt material to evolving project pipelines.
  

• Education: Bachelors Degree in Engineering Computer Science Information Technology or a related field.
  
• Experience: 612 years of overall professional experience combining corporate training technical education data engineering or senior database administration roles.
  
  

• Databricks & Spark Ecosystem: Strong hands-on proficiency with Databricks Apache Spark (PySpark/Spark SQL) Delta Lake ACID transactions data optimization techniques (Z-Ordering caching) and Lakehouse governance (Unity Catalog).
  
• Database Systems & Languages: Advanced mastery of SQL and PL-SQL. Proficient with Oracle DB engines MySQL SQL Server and PostgreSQL. Strong understanding of query optimization and database tuning.
  
• Cloud Ecosystems: Strong conceptual and hands-on familiarity with Microsoft Azure Data tracks (ADF ADLS Gen2) Google Cloud infrastructure (BigQuery) and basic AWS resources.
  
• Data Warehousing & ETL: Practical knowledge of Snowflake or Google BigQuery analytics alongside legacy Informatica PowerCenter workflow patterns.
  
• Programming & Automation: Strong proficiency in Python (especially for data manipulation via Pandas/PySpark). Familiarity with Core Java basics or C paired with a solid understanding of Windows and Unix/Linux shell scripting environments.
  

• Databricks Certified Data Engineer Associate / Professional
  
• Microsoft Certified: Azure Data Engineer Associate (DP-203)
  
• Oracle Certified Professional (OCP) / Oracle Certified Associate (OCA)