Delhi School of Skill Development (DSSD) – The AI Gurukul

Location:
Rohini, New Delhi (Main Centre) Employment Type: Full-Time Work Mode: On-site Company Description Delhi School of Skill Development (DSSD) – The AI Gurukul, established in 2015, is a future-focused skill development institution dedicated to preparing individuals for careers in the evolving digital economy. Specializing in Data Analytics, Data Science, Business Intelligence, Digital Marketing, and Artificial Intelligence, DSSD delivers industry-oriented training programmes designed to bridge the gap between theoretical knowledge and practical industry requirements. Our training methodology emphasizes hands-on implementation, real-world datasets, business case studies, live projects, and AI-powered workflows. Through structured mentorship and practical exposure, we aim to develop professionals equipped with the technical competencies and analytical thinking required to succeed in today's data-driven economy.

Job Description
We are looking for a technically proficient and passionate Data Analytics Trainer to join our academic team at our Main Centre in Rohini, New Delhi. The selected candidate will be responsible for delivering structured, instructor-led training in Data Analytics and Business Intelligence technologies, including Advanced Microsoft Excel, SQL, Power BI, Tableau, Python, Statistics, and AI-powered productivity tools. The role requires strong hands-on technical expertise, excellent teaching and communication skills, and the ability to translate complex concepts into simple, practical, and engaging learning experiences. The candidate will independently conduct classroom and laboratory sessions, develop training materials, design assignments and real-world case studies, assess learner performance, and mentor students preparing for careers in Data Analytics, MIS, and Business Intelligence.

Key Responsibilities
Technical Training and Classroom Delivery
• Deliver structured training programmes in Advanced Excel, SQL Server (T-SQL), Power BI, Tableau, Python, Statistics, and Google Looker Studio.
• Teach Advanced Excel concepts, including advanced formulas, logical functions, lookup functions, Pivot Tables, Power Query, Power Pivot, VBA, and Macros.
• Conduct SQL training covering database fundamentals, DDL, DML, DQL, joins, subqueries, CTEs, window functions, aggregate functions, stored procedures, views, and triggers.
• Deliver Power BI training covering Power Query Editor, ETL, data transformation, data modelling, Star Schema, DAX, calculated columns, measures, and dashboard development.
• Teach Tableau concepts, including data connections, data preparation, joins, relationships, data blending, calculated fields, parameters, filters, and interactive visualisations.
• Train students in Python for Data Analytics using Pandas, NumPy, Matplotlib, and Seaborn.
• Teach statistical concepts, including descriptive statistics, probability, data distributions, outlier detection, correlation, and regression analysis.
• Conduct practical demonstrations and guide learners in implementing concepts using real-world datasets. Curriculum Development and Training Material
• Develop, structure, and update Data Analytics curricula in alignment with industry requirements.
• Prepare lesson plans, presentations, assignments, practical exercises, assessments, and technical learning resources.




• Create realistic datasets and business case studies for Excel, SQL, Power BI, Tableau, and Python.
• Develop topic-wise practice materials, interview-oriented questions, and project assignments.
• Ensure training content progresses logically from fundamental concepts to advanced applications.
• Continuously improve teaching materials based on learner performance and industry developments. Projects and Practical Implementation
• Design and conduct hands-on projects based on real-world business scenarios.
• Guide learners through data cleaning, data transformation, exploratory data analysis, data modelling, visualisation, and insight generation.
• Develop case studies across sales, retail, finance, HR, customer analytics, and business operations.
• Mentor learners in developing Excel reports, SQL solutions, Power BI dashboards, Tableau visualisations, and Python-based analytical projects.
• Evaluate project submissions based on technical accuracy, analytical thinking, and practical implementation. AI and Emerging Technologies
• Introduce AI-powered tools and their applications in modern analytics workflows.
• Demonstrate practical applications of ChatGPT, Claude, Google Gemini, Julius AI, and other relevant AI tools.
• Demonstrate AI-assisted SQL queries, Python coding, data exploration, formula development, documentation, and analytical problem-solving.
• Introduce prompt engineering and AI-based productivity techniques.
• Keep training content updated with emerging technologies and responsible AI practices. Student Mentorship and Career Preparation
• Conduct practical examinations, assignments, technical assessments, and doubt-clearing sessions.
• Monitor student progress and provide structured feedback.
• Prepare learners for Data Analyst, MIS Executive, MIS Analyst, and Business Analyst positions.
• Conduct technical interview preparation covering Excel, SQL, Power BI, Python, Tableau, and analytical problem-solving.
• Mentor students in developing industry-oriented projects and professional portfolios.
• Strengthen students' logical reasoning, analytical thinking, communication, and workplace readiness. Academic Coordination
• Coordinate with the academic team for the effective execution of training programmes.
• Maintain attendance, assessment records, student performance reports, and academic documentation.
• Participate in academic reviews, faculty meetings, workshops, masterclasses, and bootcamps.
• Contribute to curriculum enhancement and institutional skill development initiatives.
• Maintain a professional, disciplined, and learner-centric classroom environment. Required Qualifications and Technical Skills Educational

Qualifications:
• Bachelor's or Master's degree in Computer Science, Information Technology, Data Analytics, Statistics, Mathematics, Engineering, or a related discipline.
• Relevant technical certifications will be an added advantage. Core Technical Competencies: Advanced Microsoft Excel:
• Advanced formulas and functions, IF,



Nested IF, AND, OR, SUMIFS, and COUNTIFS.
• VLOOKUP, HLOOKUP, XLOOKUP, and INDEX-MATCH.
• Pivot Tables and Pivot Charts.
• Data cleaning, conditional formatting, and data validation.
• Power Query, Power Pivot, VBA, and Macros. SQL and Database Management:
• Microsoft SQL Server and SSMS.
• T-SQL and database fundamentals.
• Joins, subqueries, CTEs, and window functions.
• GROUP BY, HAVING, CASE statements, and aggregate functions.
• Views, stored procedures, triggers, and data manipulation. Power BI:
• Power BI Desktop and Power Query Editor.
• ETL and data transformation.
• Data modelling, relationships, and Star Schema.
• DAX, measures, and calculated columns.
• Interactive dashboards and business reporting. Tableau:
• Tableau Desktop and data connections.
• Data Interpreter and data preparation.
• Joins, relationships, and data blending.
• Calculated fields, parameters, and filters.
• Dashboard development and data visualisation. Python and Statistics:
• Python programming fundamentals.
• Pandas and NumPy.
• Data cleaning and exploratory data analysis.
• Matplotlib and Seaborn.
• Descriptive statistics, probability, correlation, and regression. Additional Tools: Google Looker Studio, ChatGPT, Claude, Gemini, Julius AI, and other AI-powered productivity and analytics platforms. Experience and Preferred Competencies
• Minimum 2-3 years of relevant experience in Data Analytics, Business Intelligence, MIS, technical training, or academic instruction preferred.
• Previous experience delivering classroom training in Excel, SQL, Power BI, Tableau, or Python.
• Strong hands-on knowledge of analytical tools and databases.
• Ability to independently prepare lesson plans, assignments, datasets, and project-based exercises.
• Experience teaching students at beginner and intermediate levels.
• Strong verbal communication, presentation, classroom management, and mentoring skills.
• Ability to simplify complex technical concepts and demonstrate their practical applications.
• A passion for teaching, continuous learning, and developing industry-ready professionals. Ideal Candidate Profile We are looking for someone who possesses strong practical implementation skills rather than just theoretical knowledge. The ideal candidate should be capable of independently managing classroom sessions and practical laboratory training, understanding the complete data analytics lifecycle, developing realistic datasets and business case studies, and mentoring students for industry opportunities. The candidate should take ownership of learner progress, demonstrate adaptability towards emerging technologies, and actively contribute to curriculum development and academic excellence. Why Join DSSD?
• Opportunity to work with an established skill development institution founded in 2015.
• Exposure to industry-oriented Data Analytics and AI training programmes.
• Opportunity to design curricula, develop practical projects, and contribute to academic initiatives.
• Collaborative academic environment focused on practical learning and student development.
• Chance to work with emerging AI tools and modern analytics technologies. Join DSSD – The AI Gurukul and contribute to developing the next generation of Data Analytics and Business Intelligence professionals.

📌 Data Analytics Trainer (India)
🏢 Delhi School of Skill Development
📍 India