From System Engineer to Data Analyst: Aishwarya’s Career Transition

Career breaks can feel intimidating especially when trying to re-enter a fast-evolving field like data analytics. But inspiring stories like Aishwarya’s show that with the right training, consistent practice, and proper guidance, a successful comeback is absolutely possible. After a 9-year career gap, she transitioned from a former System Engineer at TCS to landing a Data Analyst role at Autobus. In this interview-style article, she shares her honest experience of upskilling with DataMites, overcoming challenges, preparing for interviews, and restarting her professional journey with confidence.

She highlights her learning process, tools she mastered, project experiences, interview preparation strategies, and real insights helpful for anyone pursuing data analyst courses, or exploring an offline data analyst institute in Coimbatore or online programs offered by DataMites.

Aishwarya’s Journey to Becoming a Data Analyst

Aishwarya’s inspiring journey from a career gap to becoming a Data Analyst shows how quality training can transform careers. Discover how DataMites and top IT courses in Coimbatore help learners build skills and achieve job success.

1. Can you tell us a little about yourself and your background?

I previously worked as a System Engineer at TCS for two years. Due to personal reasons, I had to take a long career break of almost nine years. But I always had interest and some knowledge about data, so I decided to re-enter the workforce by learning data analytics.

2. What made you choose DataMites for your Data Analyst training?

My sister studied at DataMites and successfully got placed. That gave me confidence that the training is effective. So I joined the Certified Data Analyst (CDA) course, hoping it would help me restart my career and it definitely did.

3. Was your course online or offline?

My course was completely online. The sessions were very interactive and the trainers explained every concept clearly from basics to advanced topics.

4. How was your experience learning Python and data analysis techniques?

It was excellent. Even though I had some prior understanding, DataMites helped me understand how to work with data more efficiently and professionally. The trainers guided us step-by-step on project work, data handling, and real-time analytics.

5. How many hours did you dedicate to learning daily?

Around 4–5 hours every day including attending sessions and practicing afterwards.

Refer to the articles below:

• How to Learn SQL for Data Analysis
• Correlation vs Covariance for Analysis
• Top 5 Matplotlib Projects in Python to Practice for Analysis

6. Did you refer any study materials apart from DataMites content?

Mostly DataMites’ materials. Occasionally, I checked YouTube for doubts, but DataMites’ resources covered almost everything.

7. Can you share more about the internship projects you worked on?

My projects mainly involved:

• Data cleaning using Python
• Exploratory Data Analysis using Excel
• Visualization using Power BI and Matplotlib
• I completed around 2–3 projects which gave me strong hands-on experience.

8. How were your mock interview sessions?

Mock interviews were tough but very helpful. I attended multiple mocks and finally achieved a job-ready score of 5.8, after which I started getting interview calls.

9. How did you prepare for actual job interviews?

I referred to multiple YouTube channels like “Learn with Gigs” and others related to Power BI, Python, and EDA. They helped me understand real interview patterns and problem-solving methods.

10. How many real interviews did you attend?

I attended two interviews, and I cleared the second one at Autobus.

11. What kind of questions were asked in the interview?

The interview mainly covered:

Basic questions on Python, Excel, Power BI, and SQL

• Excel formulas
• SQL queries
• Group By in Python
• Basic visualizations

Project-related questions like techniques used, insights generated, reasons for data cleaning steps, etc.

12. Were you asked to implement any code during the interview?

No live coding. They mostly checked my conceptual knowledge and project understanding.

13. What was the interview process like?

It was a single round focusing on:

• My project explanation
• Data cleaning steps
• Excel formulas
• SQL basics
• Visualization insights

14. What tools will you be using in your new job at Autobus?

Excel, Python, SQL, and Power BI. The company will provide three months of training before assigning live tasks.

15. What areas should aspiring data analysts focus on?

• Strengthen basic concepts
• Don’t ignore simple questions
• Practice Python (especially groupby, null handling, duplicates removal, visualization)
• Understand SQL and Excel thoroughly
• Build strong, clear project explanations

16. How was your resume prepared?

I prepared my resume initially, and then the DataMites placement team rewrote it in ATS format. After that, I started receiving more interview calls.

17. Can you share insights from one of your toughest interview experiences?

One American company gave me:

• An online test
• A Python + Excel assessment
• I handled:
• Data cleaning
• Removing duplicates
• Null value treatment
• GroupBy
• Matplotlib visualizations

They asked why I took certain steps, the business meaning behind decisions, and insights from visualizations.

18. Is your new job remote or hybrid?

It is a hybrid job with an online interview process.

Key Highlights from the journey of Aishwarya:

Here are the highlights from the journey of Aishwarya that reflect the true essence of many DataMites success stories, where resilience meets the right mentorship.

1. Successful Career Restart After a Long Break: Aishwarya returned to the workforce after a 9-year gap and transitioned from a System Engineer to a Data Analyst with the support of DataMites’ structured training.
2. Strong Technical Upskilling Through Online Training: She gained confidence in essential tools like Python, Excel, SQL, and Power BI through clear, well-guided online sessions.
3. Hands-On Project Experience Boosted Practical Skills: Completing 2–3 real-time internship projects strengthened her abilities in data cleaning, EDA, and visualization.
4. Effective Interview Preparation and Mock Assessments: Mock interviews, a job-ready score of 5.8, and additional learning via YouTube channels helped her crack real interviews with ease.
5. Placement Support Enhanced Recruitment Opportunities: The DataMites placement team’s ATS-friendly resume rewriting significantly improved her interview call rate.
6. Successful Placement with Training Support at Autobus: She secured a Data Analyst role at Autobus, which offers three months of training highlighting the importance of data analyst skills, consistent practice, and strong mentorship.

Aishwarya’s journey from a 9-year career gap to becoming a Data Analyst highlights the power of structured learning, hands-on projects, and dedicated practice. Her success at DataMites inspires others to upskill, build confidence, and achieve rewarding careers in data analytics.

Refer to the articles below:

• Harsh’s career transition from non-tech background to data analyst
• Nupur's Journey from fresher to data analyst
• Farjad's Journey as a Lead Data Analyst

DataMites Institute is a leading IT training center offering best data analyst institute in Coimbatore, along with comprehensive programs in Data Science, Artificial Intelligence, Machine Learning, Python, and IoT. With hands-on learning, real-time projects, internships, and strong placement support, DataMites equips learners with practical skills and globally recognized certifications from IABAC and NASSCOM FutureSkills.

In addition to its data analyst training in Chennai, DataMites provides industry-focused and flexible training across major Indian cities including Bangalore, Pune, Coimbatore, Hyderabad, Ahmedabad, and Delhi empowering students to build successful careers in data analytics and emerging technologies.