Data Engineering & Data Visualisation Instructor

About Newton School of Technology: NST is a new-age institution redefining technical education in India. Founded by IIT alumni, NST offers a four-year B.Tech programme in Computer Science and AI, emphasising hands-on learning, industry integration, and real-world problem-solving.
With industry-focused projects, practical learning opportunities, and exposure to emerging technologies, NST aims to prepare students for advanced technology careers. Its faculty brings together academic expertise and industry experience to create an engaging, outcome-driven learning environment.
About the Role: We are looking for an experienced Data Engineering & Data Visualisation Instructor to join our academic team in Pune.
This role combines technical expertise with teaching, mentoring, and curriculum development. The ideal candidate will have strong practical knowledge of databases, SQL, data engineering, and data visualisation, along with the ability to translate complex technical concepts into engaging, hands-on learning experiences.
You will design and deliver industry-relevant courses, mentor students through practical assignments and capstone projects, and help develop the next generation of data professionals.
Key Responsibilities:
1. Curriculum Development
Design and develop course content, lesson plans, lab exercises, and assessments covering DBMS, data engineering, and data visualisation.
Develop practical assignments and projects aligned with industry practices and current technologies.
Continuously update curriculum content to reflect emerging trends in databases, business intelligence, analytics, and cloud technologies.
2. Teaching and Training
Deliver lectures, workshops, and hands-on sessions on database management systems, SQL, data modelling, and database design.
Teach relational database concepts, normalisation, indexing, query optimisation, transactions, and database security.
Train students in Python, data processing, ETL/ELT concepts, and introductory data pipeline development.
Teach data visualisation and reporting using Power BI, Tableau, Excel, or equivalent tools.
Introduce students to data warehousing, cloud databases, and relevant industry use cases.
3. Practical Projects and Industry Application
Design real-world projects involving data collection, transformation, analysis, and visualisation.
Develop capstone projects that integrate data engineering, business intelligence, and, where relevant, AI/ML applications.
Incorporate industry scenarios and datasets to help students develop practical problem-solving skills.
Guide students in building portfolio-ready projects that demonstrate their technical capabilities.
4. Student Assessment and Mentorship
Develop quizzes, assignments, coding exercises, and project-based assessments.
Evaluate student performance and provide actionable feedback.
Mentor students in debugging, troubleshooting, analytical thinking, and technical problem-solving.
Support students in building career-ready skills and preparing for data engineering, database, and analytics roles.
5. Industry Collaboration
Stay updated on industry tools, technologies, and best practices.
Conduct technical workshops, guest sessions, hackathons, and project demonstrations.
Collaborate with other faculty members to integrate data concepts into multidisciplinary projects.
Contribute to continuous improvement of teaching methodologies and learning outcomes.
Qualifications and Experience :
Master's degree in Computer Science, Information Technology, Data Science, or a related field or Phd in computer science
Minimum 3 years of relevant professional experience in data engineering, database development, BI/data analytics, or related technical roles.
Demonstrated ability to explain technical concepts clearly and mentor others.
Prior teaching, training, mentoring, or technical enablement experience is preferred.
Technical Skills
Strong proficiency in SQL and at least one major relational database, such as PostgreSQL, MySQL, or Microsoft SQL Server.
Good understanding of database design, data modelling, normalisation, indexing, query optimisation, and performance tuning.
Working knowledge of Python for data processing and automation.
Practical experience with data visualisation tools such as Power BI or Tableau.
Understanding of ETL/ELT workflows, data pipelines, and data warehousing concepts.
Familiarity with NoSQL databases such as MongoDB is an advantage.
Exposure to cloud data platforms and services, such as AWS, Azure, or Google Cloud, is preferred.
Strong communication, presentation, and problem-solving skills.
What We Are Looking For
A hands-on technology professional who enjoys teaching and mentoring.
Someone who can bridge the gap between theoretical concepts and real-world industry applications.
A candidate who can build engaging learning experiences and guide students through practical projects.
A collaborative individual who is passionate about developing future-ready technology talent.

Work arrangement
No