From Curiosity to Career: Shashank’s Path into Data Engineering

Shashank’s journey from a Computer Science fresher to a data engineer at BizViz Technologies Pvt Ltd highlights how curiosity, persistence, and structured learning can transform challenges into career opportunities. Initially facing difficulties in communication and practical application of data science concepts, he leveraged the comprehensive training at DataMites, mastering Python, statistics, machine learning, NLP, and data visualization tools.

By working on real-world projects like House Price Prediction and a Telecom Prediction Project for a European client, Shashank applied theoretical knowledge to practical scenarios, building both skills and confidence. Aspiring data professionals can look to Shashank’s path as a testament to dedication, learning, and structured growth in the data field, making it an inspiring DataMites success story.

From Computer Science Fresher to Data Engineer: Shashank’s DataMites Journey

This Q&A showcases Shashank’s transition from a Computer Science fresher to a Data Engineer, detailing his learning experience, hands-on projects, mock interviews, and successful placement through DataMites.

Q1. Can you introduce yourself and your academic background?

My name is Shashank. I am from Hassan and recently completed my Bachelor’s degree in Computer Science and Engineering from a government engineering college. During my final year, I developed a strong interest in data science and machine learning, which led me to pursue specialized training after graduation.

Q2. What sparked your interest in data science?

My interest began while working on a final-year project titled Crop Production Based on the Indian Agriculture System. Guidance from my seniors and exposure to real-world data applications made me realize the importance of data science, which motivated me to pursue it further.

Q3. How did you discover DataMites as your training institute?

After completing graduation, I was searching for the right training institute. Through Google search, I found DataMites and decided to join based on its credibility, curriculum, and strong placement support.

Q4. When did you join the DataMites course and what did you learn?

I joined in July 2023. The training started with Python, where I learned beyond the basics I already knew. Then I explored statistics, machine learning algorithms, NLP, data visualization tools like Tableau and Power BI, and hyperparameter tuning for model optimization.

Q5. Was it easy to adapt to statistics and machine learning as a fresher?

Initially, statistics was a little challenging. However, with structured training and consistent practice, I was able to understand the concepts better and apply them effectively.

Q6. How long did it take for you to complete the course and get placed?

The course took around six to eight months. It took me about four to five additional months to secure a job, during which I focused on mock interviews, improving technical knowledge, and building confidence.

Q7. What challenges did you face during mock interviews?

I attempted three mock interviews. Being from a Kannada medium background, my main struggle was communication in English. Although I knew the answers, I initially found it hard to express them properly. Over time, I improved my confidence and delivery.

Q8. How important is communication compared to technical skills in data science?

While communication matters, analytical and technical skills play a bigger role in data science. Employers focus more on your ability to solve problems using machine learning and data analysis rather than fluency in English.

Q9. How many real interviews did you attend before getting selected?

I attended two interviews. In my first interview, I cleared the aptitude and initial technical round but was rejected in the second technical round. In the second interview, I succeeded and secured the job, getting placed at BizViz Technologies Pvt Ltd.

Q10. What went wrong in your first interview?

The first interview required coding tasks using Pandas and handling Excel data. While I cleared the first round, I struggled with certain tasks in the second round, such as creating and manipulating multiple sheets in Excel through Python. This was a learning point for me.

Q11. What projects did you complete during your training?

I worked on several projects; the main ones are:

• House Price Prediction
• Telecom Prediction Project (a live project from a European client)

These projects gave me exposure to real-world datasets and problem-solving.

Q12. How did the placement assistance (PAT) at DataMites support you?

The PAT team helped me prepare through mock interviews, resume support, and job-ready tests. After clearing the mock assessment with the required score, they connected me with companies and guided me with interview feedback.

Q13. How did you overcome language barriers and improve communication?

I practiced regularly using communication applications, watched technical videos on YouTube, and gradually improved my presentation. DataMites now also provides soft skills training, which helps students enhance English and professional communication.

Q14. What do you believe were the key factors behind your success?

Consistent hard work, never giving up, and learning from failures were the key factors. As I believe, there is no shortcut to success. Staying dedicated and continuously improving helped me land my first job.

Q15. What advice would you give to other freshers aspiring to become data scientists?

• Stay consistent and practice daily.
• Focus on mastering Python, statistics, and machine learning fundamentals.
• Take mock interviews seriously: they help in identifying weak areas.
• Don’t let language barriers stop you; confidence matters more than fluency.
• Be patient, as placements can take time, but persistence pays off.

Refer to these articles:

• How Parag Thakur Built His Career in Data Science
• Vinay Gaikwad’s Journey in Freelance Data Science
• Freelancing in Data Science: Samapika Singh’s Insights

Shashank’s Path to Data Engineering: Key Insights and Achievements

Shashank’s journey showcases how dedication, hands-on projects, and guided training can help a fresher transition into a successful data engineering career. His story highlights the importance of persistence, practical learning, and continuous skill development in achieving professional goals.

• Shashank successfully transitioned from a Computer Science fresher to a Data Engineer through dedicated training at DataMites.
• He built expertise in Python programming, statistics, machine learning algorithms, natural language processing (NLP), and data visualization tools like Tableau and Power BI.
• Hands-on experience with projects like House Price Prediction and a Telecom Prediction Project for a European client helped him apply theoretical knowledge to real-world problems.
• He initially faced challenges in communication and conveying technical knowledge, which he overcame through consistent practice and mentorship.
• Mock interviews and repeated assessments improved his confidence, interview skills, and technical readiness.
• Shashank emphasized persistence and dedication, showing that repeated attempts and continuous learning lead to eventual success.
• He utilized online resources, DataMites portal materials, and YouTube tutorials to strengthen his understanding of core concepts.
• Overcoming early setbacks in mock interviews reinforced his problem-solving approach and depth of knowledge in machine learning and data analysis.
• His story highlights the importance of applied learning through live projects in building practical experience for placements.
• Structured guidance from mentors and a well-planned study approach enabled him to bridge gaps between academic learning and industry requirements.
• Shashank’s journey proves that freshers from regional colleges can excel in competitive fields like data engineering with the right strategy.
• The experience underscores that communication fluency is helpful but not a barrier if technical skills and analytical abilities are strong.
• Shashank serves as an inspiring example for beginners, showing that dedication, structured training, and real-world practice can achieve career goals.

Refer to these articles:

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

Shashank’s journey shows that transitioning from a fresher in Computer Science to a skilled data professional is entirely possible with curiosity, dedication, and consistent effort. By focusing on core tools like Python, statistics, and machine learning, and gaining hands-on experience with real-world projects, he proved that structured learning can open doors in data engineering and analytics. If you’re looking to make a similar leap, take inspiration from his path: start with foundational skills, work on practical projects, and gradually build expertise in advanced analytics and data processing.

With Shashank’s journey as an example, now is the perfect opportunity to consider a career in Data Engineering, one of the fastest-growing and most in-demand fields in tech. As organizations increasingly rely on data-driven decisions, the need for skilled professionals continues to rise. According to Mordor Intelligence, the global data science platform market is expected to grow from USD 111.23 billion in 2025 to USD 275.67 billion by 2030 at a CAGR of 21.43%, driven by rising demand for integrated AI and data solutions. Enrolling in a top-rated offline Data Engineering course in Bangalore, Chennai, Hyderabad, Pune, Mumbai, or Delhi can open significant career opportunities and equip you with the skills needed to excel in this dynamic field.

Coming from a Computer Science background, Shashank decided to pursue a career in data roles. He joined a comprehensive Data Science course at DataMites Pune, where he gained hands-on expertise in Python, statistics, machine learning, NLP, and data visualization tools like Tableau and Power BI. Through consistent learning, offline classroom sessions, and capstone projects, he built both the skills and confidence to transition successfully. His training was strengthened by globally recognized certifications from IABAC and NASSCOM FutureSkills.

Today, Shashank grows in data roles, applying his technical skills to solve real-world challenges. His journey demonstrates how structured learning, mentorship, and hands-on experience can make a career transition both achievable and rewarding. Join thousands of learners who are equipping themselves with the skills that the tech industry demands today.

For those in Tamil Nadu, enrolling in a Data Engineer Course in Chennai offers in-depth technical training, hands-on projects, and career guidance to help launch your career.

Learners in Telangana can benefit from a Data Engineer Course in Hyderabad, offering the same industry-driven curriculum and dedicated career support, equipping you with the skills to grow in the fast-expanding data field.