Mid-Level Technical Trainer

Key Responsibilities

1. Curriculum & Training Design

• Analyze client-specific product/domain requirements to define learning objectives, outcomes, and success metrics.
• Develop modular, role-based training materials (slide decks, hands-on labs, code samples, quizzes) covering:

• Databases:

  Relational (PostgreSQL, MS SQL Server), NoSQL (MongoDB, Cassandra)

• Programming & Frameworks:

  Python (including ML pipelines), Java, GoLang, C#/.NET Core, Blazor

• Front-end:

  ReactJS (components, state management, hooks)

• Big Data & Messaging:

  HDFS (core commands, shell scripting), Apache Kafka, RabbitMQ, MQTT

• Data Analytics:

  ETL concepts, Pandas-based data wrangling, Matplotlib visualizations
• Continuously iterate on training content based on learner feedback, technology updates, and best practices.

2. Hands-On Development & Domain Engagement

• Collaborate with client SMEs, product owners, and engineering teams to understand architecture, codebase standards, and deployment pipelines.
• Build proof-of-concepts, reference implementations, and sample mini-projects that align with the training curriculum.
• Troubleshoot and optimize sample code (both back-end and front-end) to illustrate best practices in performance, scalability, and maintainability.

3. Instruction & Mentoring

• Lead instructor-led sessions (in-person or remote) covering theory (20–30%), code walkthroughs (30%), and hands-on labs (40–50%).
• Provide one-on-one mentoring: review trainee code, offer constructive feedback, troubleshoot roadblocks, and ensure skill acquisition.
• Design assessment mechanisms (quizzes, coding assignments, capstone projects) to evaluate learner readiness and provide remediation as needed.

4. Onboarding & Trainee Progress Tracking

• Create and maintain a structured onboarding roadmap for college graduates, including prerequisites, recommended readings, and milestone checklists.
• Monitor trainee progress through weekly checkpoints, code reviews, and performance metrics—adjust training pace or content accordingly.

5. Knowledge Management & Continuous Improvement

• Maintain and update a centralized repository (internal wiki or LMS) of training artifacts, best practices, troubleshooting guides, and FAQs.
• Host regular “Knowledge-Sharing” sessions or brown-bag workshops to showcase trending technologies, emerging frameworks, and industry insights.
• Solicit and analyse post-training feedback to refine content, delivery style, and instructional tools.

6. Collaboration & Stakeholder Communication

• Work closely with HR/Talent Acquisition to align training agendas with hiring timelines and candidate profiles.
• Coordinate with senior architects, DevOps, QA, and UX/UI teams to ensure consistent messaging about coding standards, development processes, and testing methodologies.
• Provide periodic status updates and training metrics (enrolment, completion rates, assessment scores) to project sponsors or leadership.

Qualifications & Skills

Experience & Background

• Total Professional Experience:

  4–6 years in software development, technical consulting, or training roles.

• Development Expertise:

  At least 3 years of hands-on coding in two or more of the following domains:

• Back-End: Python (including basic ML pipelines), Java (Spring/REST), GoLang, C#/.NET Core (Blazor)

• Front-End: ReactJS (functional components, state/hooks, component composition)

• Data Storage: PostgreSQL, MS SQL Server, NoSQL (MongoDB, Cassandra)

• Big Data & Messaging: HDFS (Bash/CLI), Apache Kafka (producer/consumer patterns), RabbitMQ, MQTT

• Data Analytics: Pandas-based ETL, basic visualization with Matplotlib

Core Competencies

1. Instructional Design & Delivery

• Proven experience designing and delivering technical training sessions (classroom or virtual).
• Ability to break down complex topics into modular, digestible learning modules.

2. Full-Stack Development Acumen

• Deep understanding of software design patterns, RESTful API development, and asynchronous messaging architectures.
• Familiarity with CI/CD pipelines (Jenkins, GitLab CI) and version control best practices (Git branching, pull requests).

3. Communication & Mentoring

• Exceptional verbal and written communication skills; comfortable presenting to groups of 10–20 trainees.
• Strong interpersonal skills to provide empathetic, actionable feedback during one-on-one mentorship.

4. Analytical & Problem-Solving

• Demonstrated ability to troubleshoot production-like scenarios (performance bottlenecks, data inconsistency, messaging failures).
• Resourcefulness in researching new technologies, diagnosing root causes, and implementing practical solutions.

5. Adaptability & Continuous Learning

• Genuine passion for staying current with emerging trends (cloud-native patterns, container orchestration, advanced ML libraries).
• Willingness to rapidly upskill in unfamiliar frameworks or tools based on evolving client requirements.

Preferred Qualifications (Nice to Have)

• Domain Exposure:

  Prior experience working in financial services, healthcare, or IoT industries—familiarity with domain-specific compliance or data workflows.

• Cloud Platform Experience:

  Hands-on knowledge of deploying/troubleshooting workloads on AWS, Azure, or Google Cloud (EC2, S3, Azure App Services, GCP Compute Engine).

• Certification:

  Any relevant credentials such as:
• Oracle Certified Professional – Java SE
• Microsoft Certified: Azure Developer Associate
• Confluent Certified Developer for Apache Kafka

• Public Speaking & Content Creation:

  Experience authoring technical blogs, whitepapers, or delivering webinars at college campuses or meetups.

• Instructional Technology Tools:

  Familiarity with Learning Management Systems (e.g., Moodle, Canvas) and authoring tools (Articulate, Captivate).