Chandana’s Journey from Fresher to Data Engineer

Starting a career in the data field can be challenging for fresh graduates as they move from academic learning to practical industry requirements. After completing her MCA in 2025, Ratakonda Chandana decided to build her career in the data field and joined DataMites to strengthen her technical skills and gain practical knowledge.

During her training, Chandana learned SQL, Python, Power BI, and Orange while working on two capstone projects and one client project. She also used mock interviews, self-learning resources, and placement support to prepare for technical interviews. Through the DataMites placement process, she secured an opportunity to join Diacto Technologies as a Data Engineer. Her DataMites Success Story highlights her transition from a fresher to a professional in the data field.

Insights into Chandana’s DataMites Learning and Career Journey

Ratakonda Chandana shares her DataMites learning journey, covering technical training in Python, SQL, Power BI, and practical projects. She also discusses mock interviews, self-learning, placement support, and how her training helped her prepare for a Data Engineer role at Diacto Technologies.

Q1. Can you tell us about yourself and your journey into the data field?

My name is Ratakonda Chandana, and I completed my MCA in 2025. I wanted to build my career in the data field, so I joined DataMites to develop my technical skills and practical knowledge. I completed the course offline at the Bangalore centre, where I learned SQL, Python, and Power BI. Through the training and placement process, I secured an opportunity with Diacto Technologies as a Data Engineer. 

Q2. What motivated you to choose a career in the data field?

During my academics, I developed an interest in technology and problem-solving. I became interested in how data can be used to understand information and support business decisions. This motivated me to choose the data field and join DataMites to build my practical skills.

Q3. What technologies and topics did you learn at DataMites?

I learned technologies such as SQL, Python programming, Power BI, and Orange. These helped me understand different tools and their practical applications. The hands-on training also helped me gain confidence in working with these technologies.

Q4. What kind of projects did you work on during the course?

I worked on three projects in total. Two were capstone projects and one was a client project. These projects gave me hands-on experience and helped me understand how the concepts I learned could be applied to practical problems.

Q5. How did you prepare and revise the topics you learned?

I used the DataMites LMS portal for preparation. The recorded sessions helped me revise the topics covered during training. I also used platforms such as ChatGPT and YouTube for self-learning and to understand new technologies and concepts.

Q6. How many mock interviews did you attend?

I attended three mock interviews. Each mock interview helped me understand where I needed to improve. I received different technical and coding questions, which encouraged me to study the topics in greater depth. I received a score of 6.5 in my third mock interview.

Q7. How did the DataMites placement team help you with interview preparation?

The placement team supported me with resume building and guided me on the topics I needed to prepare for client interviews. They helped me understand what areas I should focus on and supported me throughout the interview preparation process.

Q8. How did your DataMites training help you prepare for the Data Engineer interview at Diacto Technologies?

The training gave me a strong foundation in technical concepts. The guidance from DataMites helped me understand what I needed to learn and how to prepare for interviews. The practical training and mock interviews also helped me become more confident while facing technical questions.

Q9. What type of scenario-based questions were asked during the interview?

The interviewer asked questions that tested my problem-solving and analytical thinking. For example, I was asked a scenario involving estimating the number of white cars in my city and determining how many were sold. These questions required me to think logically and explain my approach.

Q10. Did you learn anything beyond the DataMites curriculum?

Yes. Since Data Engineering is different from Data Analytics, I explored additional topics through self-study. One of the areas I learned was APIs, which helped me understand new concepts related to the Data Engineering field.

Q11. What advice would you like to give to freshers?

Freshers should try to learn concepts in depth rather than limiting themselves to the basics. Competition is high, so when an opportunity comes, they should be prepared to make the most of it. Consistent learning, practical experience, and strong technical knowledge can help them prepare better for data science job opportunities.

Q12. How did the DataMites placement process help you get your opportunity at Diacto Technologies?

The placement process gave me an opportunity to attend interviews and apply the skills I had developed during the course. The placement team's support with resume preparation, interview topics, and mock interviews helped me become more confident throughout the process.

Q13. What is your biggest takeaway from your DataMites journey?

My biggest takeaway is the importance of continuous learning and practical experience. The course helped me develop technical knowledge, while the projects, mock interviews, and placement support helped me apply that knowledge and prepare for real interviews. It gave me the confidence to start my career in the Data Engineering field.

Refer to these articles : 

• Subham’s Journey from Fresher to Becoming a Data Engineer
• Venkata’s Journey from Fresher to Successful Data Engineer
• From Fresher to Data Scientist: Sarumathi’s Success Story

Key Takeaways from Chandana’s Success Story

Ratakonda Chandana’s journey highlights the importance of practical learning, continuous preparation, and confidence when building a career in data engineering. Her experience offers several useful takeaways for aspiring data professionals:

• Strong Academic Foundation: Chandana completed her MCA in 2025 and chose to build her career in the data field.
• Practical Data Analytics Training: Her DataMites training helped her develop skills in Python, SQL, Power BI, and Orange.
• Hands-On Project Experience: She completed two capstone projects and one client project, gaining practical exposure.
• Consistent Self-Learning: She used the DataMites LMS, ChatGPT, YouTube, and other platforms to revise concepts and learn new technologies.
• Mock Interview Preparation: Three mock interviews helped her improve her technical knowledge and identify areas that needed more preparation.
• Placement Support: The DataMites placement team supported her with resume building and guidance on topics to prepare for client interviews.
• Technical Interview Readiness: Her interview preparation helped her handle Python, SQL, coding, and scenario-based technical questions.
• Learning Beyond the Curriculum: She independently explored APIs and other topics related to Data Engineering beyond her Data Analytics training.
• Career Opportunity: Through the DataMites placement process, Chandana secured an opportunity as a Data Engineer at Diacto Technologies.
• Advice for Freshers: Chandana encourages freshers to learn concepts in depth, strengthen practical skills, and make the most of every interview opportunity.

Refer to these articles : 

• How to Become a Data Scientist With No Experience
• Secure Data Science Pipelines: Preventing Data Leakage and Attacks
• Data Science vs Cyber Security: Which Has Better Future?

Ratakonda Chandana’s journey from an MCA graduate to a Data Engineer at Diacto Technologies shows how focused preparation can help freshers move toward their career goals. Her experience highlights the importance of understanding concepts deeply, gaining practical project experience, and preparing for technical interviews. Her story can encourage aspiring data professionals to keep learning, make use of available opportunities, and build the skills needed for their desired roles.

Building a career in data engineering requires technical skills, practical experience, and continuous learning. Ratakonda Chandana’s journey reflects the importance of developing these skills through structured training and hands-on practice. According to MarketsandMarkets, the global big data market is projected to grow from USD 324.59 billion in 2026 to USD 516.29 billion by 2031, registering a 9.7% CAGR. Exploring the best top IT courses can help learners build relevant technical skills and prepare for career opportunities in the growing data industry.

Ratakonda Chandana’s journey from an MCA graduate to a Data Engineer was supported by structured learning and practical training at DataMites. Through hands-on projects, LMS resources, mock interviews, self-learning, and placement support, she strengthened her skills in Python, SQL, Power BI, and other data-related concepts. For learners exploring a Data Science institute in Bangalore, Chandana’s experience highlights the value of practical training, continuous learning, and focused interview preparation.

Whether you are a fresher or an aspiring data professional like Ratakonda Chandana, DataMites Institute provides structured learning designed to build practical and industry-relevant skills. With 50+ offline centres and online learning options, DataMites offers Data Science courses in Hyderabad along with training opportunities in Chennai, Delhi, Mumbai, Coimbatore, Ahmedabad, Kolkata, Noida, Indore, Jaipur, Chandigarh, Kochi, Nagpur, and Bhubaneswar. Through hands-on projects, expert mentorship, internship opportunities, interview preparation, and IABAC® and NASSCOM FutureSkills® certifications, learners can develop skills relevant to the data industry.