Yasaswini’s Inspiring Transition into Data Engineering

Yasaswini’s story is a motivating example of how determination, structured training, and hands-on learning can redefine a career path. Coming from a non-technical background and working in the government sector, she chose to pivot into data science and data engineering to pursue greater professional growth. Through DataMites’ comprehensive program, she gained expertise in Python, statistics, machine learning, and SQL, turning initial challenges into opportunities for skill development.

With guidance from DataMites’ placement team, Yasaswini successfully secured a position as a Data Engineer at Helical IT Solutions, working on SQL-based data processes and ETL tools. Her journey demonstrates that with consistent effort, practical exposure, and expert mentorship, anyone regardless of background can achieve a rewarding career in data. Yasaswini’s transformation stands as a shining DataMites success story.

How Yasaswini Transitioned into a Data Engineer Role with DataMites

Yasaswini leveraged structured learning, hands-on training, and expert mentorship at DataMites to transition from a non-technical background into a Data Engineer role at Helical IT Solutions. Her journey highlights determination, skill-building, and practical experience as key drivers of career transformation.

Q1. Can you introduce yourself and tell us about your background before entering data science?

Hello, my name is Yasaswini from Tirupati. I completed my B.Sc. in Mysore and worked in the government sector for two years. However, I felt that my role had limited growth opportunities. That’s when I decided to switch my career path and move into data science, a field I found both dynamic and full of future potential.

Q2. What motivated you to choose DataMites for your data science journey?

I researched various institutes and found that DataMites had a structured program with practical exposure, hands-on projects, and valuable certifications. Their comprehensive learning modules gave me the confidence that I could successfully transition into this field even without a technical background.

Q3. When did you join DataMites, and how was your learning experience?

I joined DataMites in October 2021. The training was well-structured and covered everything from Python and statistics to machine learning and real-time projects. Although I came from a non-technical background, the trainers explained every concept clearly and guided us through practical sessions, which made the learning process enjoyable.

Q4. Was it challenging to learn technical subjects like Python and statistics?

Initially, it was quite new to me, especially Python, since I had no prior programming experience. However, with consistent practice, I started feeling comfortable after about three weeks. My background in mathematics helped me understand statistical concepts, and combined study sessions with peers made a big difference.

Q5. How did you find learning machine learning concepts?

Machine learning was challenging at first, but once I understood the logic behind it, it became one of the most fascinating parts of the course. The real-world examples and projects at DataMites helped me relate theoretical concepts to practical applications.

Q6. What kind of projects did you work on during your DataMites course?

I worked on multiple projects, including flight delay prediction, and a bank-related capstone project. These projects gave me practical exposure to regression, classification, and real-time problem-solving scenarios, which later proved extremely useful in my job.

Q7. How did DataMites support you in placement preparation?

The placement team at DataMites was very proactive. They helped me refine my resume, guided me through mock interviews, and shared openings relevant to my skill set. Their support played a crucial role in my placement at Helical IT Solutions as a Data Engineer. They were available at all times for queries, which boosted my confidence and prepared me thoroughly for the interviews.

Q8. Tell us about your placement at Helical IT Solutions.

I got placed as a Product Engineer (Data Engineer) at Helical IT Solutions in September 2022. The company develops business intelligence tools similar to Tableau but at a more affordable scale. It’s a product-based firm with a small, dynamic team, which has helped me learn a lot about data engineering and SQL-based processes.

Q9. What technologies and tools do you use in your current role?

I primarily work on SQL and ETL tools. Initially, I also explored Apache Spark as part of our project. My work involves handling data pipelines, integrating data, and ensuring it’s ready for analysis through the company’s BI product, Helical Insight.

Q10. What are the key skills every aspiring data engineer should focus on?

The most important skill is SQL; it's the foundation for all data operations. Apart from that, one should learn:

• ETL tools (like Pentaho or Talend)
• Basic Python for data handling
• Big Data tools like Apache Spark
• Understanding of databases (SQL and NoSQL)

Practicing queries regularly on SQL websites helped me strengthen my technical skills significantly.

Q11. Is it possible for freshers to become data engineers?

Absolutely yes. I’m living proof of that. Even as someone from a non-technical background, I was able to make this switch. Companies are open to hiring candidates who demonstrate solid technical understanding and project experience. Completing internships or practical training through DataMites gives candidates an edge, making them job-ready.

Q12. Does a career gap affect job opportunities in data engineering?

Not anymore. I had a few months’ gap before my placement, but it didn’t affect my chances. Employers today value practical skills and project experience over continuous employment history. As long as you can justify your gap and show learning progress during that period, it’s completely fine.

Q13. What’s the average starting salary for data engineers today?

The average salary for freshers in data engineering currently ranges around ₹6–7 LPA. However, it can go much higher depending on the company, skills, and performance in interviews. With just one year of experience, professionals often see a significant hike, even up to 100%.

Q14. What advice would you give to non-technical learners aspiring to enter data science or engineering?

Start by strengthening your basics in SQL and Python. Don’t get overwhelmed by the number of tools out there. Focus on understanding concepts first. Group study, peer discussions, and consistent practice are key. Also, don’t let a career gap or non-IT background discourage you. With dedication and the right guidance from institutes like DataMites, transitioning into this field is absolutely achievable.

Q15. How do you see your career progressing in the coming years?

Currently, I’m focusing on deepening my expertise in data engineering tools and processes. Eventually, I plan to explore machine learning and AI applications within data pipelines. Working in a product-based company gives me the opportunity to understand how data shapes intelligent systems, and I see a long, promising future ahead.

Refer to these articles:

• Sathish’s Inspiring Journey to Becoming a Data Scientist
• How Littleflower Built a Successful Career in Data Engineering
• Becoming a Senior Data Engineer: Ashish’s Success Story

Yasaswini’s Journey to Data Engineering: Key Insights with DataMites

Yasaswini’s journey highlights how structured learning, hands-on projects, and consistent effort enabled her to successfully transition from a non-technical background into a data engineering career with the guidance and support of DataMites.

• Yasaswini, from Tirupati, transitioned from a non-technical background to a successful career in data engineering.
• She completed her B.Sc. in Mysore and worked in the government sector for two years before pursuing data science.
• DataMites provided her with structured, hands-on training covering Python, statistics, machine learning, and real-world projects.
• Despite her non-technical background, consistent practice and strong mentor support helped her master technical subjects.
• Her key learning projects included flight delay prediction, diabetes classification, and a bank capstone project.
• DataMites offered dedicated placement assistance through resume guidance, mock interviews, and job referrals.
• She secured a role as a Product Engineer (Data Engineer) at Helical IT Solutions, a business intelligence firm.
• In her current role, she works extensively with SQL, ETL tools, and data pipeline processes.
• She emphasized SQL as the most crucial skill for aspiring data engineers, along with Python and Big Data tools.
• Yasaswini believes that non-technical learners and freshers can successfully enter data engineering with the right training.
• Career gaps are not a barrier if candidates can demonstrate consistent learning and practical project experience.
• Entry-level data engineering salaries average around ₹6–7 LPA, with significant growth potential after a year of experience.
• Her future goals include deepening expertise in data engineering and exploring machine learning integrations in data pipelines.
• Yasaswini credits DataMites for providing the foundation, mentorship, and placement support that helped her achieve her data career goals.

Refer to these articles:

• How to Become a Data Scientist in Bangalore?
• Data Science Course Fee in Bangalore
• How to Become a Data Scientist in Hyderabad?
• Data Science Course Fee in Hyderabad

Yasaswini’s journey shows that with focused learning, hands-on projects, and dedication, transitioning into a data engineering career is entirely achievable. Moving from a non-technical government role to a dynamic data engineering position, she demonstrates how commitment, consistent upskilling, and practical experience can help professionals excel in data-driven fields. Her story highlights the importance of building strong analytical foundations, mastering essential tools, and working on real-world projects to gain confidence and competence in the industry.

With Yasaswini’s journey as an example, now is an ideal time to explore a career in Data Engineering, one of the fastest-growing and highly sought-after domains in technology. As businesses increasingly depend on data-driven insights, the demand for skilled professionals continues to expand. Fortune Business Insights reports that the global data science platform market is expected to grow from USD 133.12 billion in 2024 to USD 776.86 billion by 2032 at a CAGR of 24.7%, with North America accounting for 27.7% of the market in 2023. Enrolling in a leading offline Data Engineering course in Pune, Bangalore, Hyderabad, Mumbai, Chennai, or Delhi can provide valuable skills and open doors to promising career opportunities in this evolving field.

With a B.Sc. in Maths, Physics, and Chemistry, Yasaswini chose to shift from her government position to a career in data engineering. She joined the Data Science course at DataMites Bangalore, gaining practical skills in Python, statistics, SQL, ETL tools, and data visualization. Through hands-on projects, structured guidance, and consistent practice, she built the expertise and confidence to step into a data engineering role. Her learning journey was further supported by globally recognized certifications from IABAC and NASSCOM FutureSkills, preparing her for a successful professional transition.

Today, Yasaswini applies her technical expertise in data engineering to handle real-world challenges effectively. Her journey highlights how structured learning, mentorship, and practical experience can make transitioning into a data career both achievable and fulfilling. Join countless learners who are gaining the skills the tech industry demands today.

For professionals in Karnataka, enrolling in a Data Engineer Course in Bangalore provides comprehensive technical training, hands-on projects, and career guidance to successfully launch your career.

Learners in Telangana can benefit from a Data Engineer Course in Hyderabad, offering the same industry-focused curriculum and dedicated career support, preparing you to excel in the rapidly growing data field.