Sanket's Inspiring Journey to Data Engineering Success at Kellogg's

Sanket's Inspiring Journey to Data Engineering Success at Kellogg's

Summary

The blog explores Sanket Vishwakarma's unconventional journey from a laid-back hostel lifestyle to becoming a Data Engineer at Kellanova (formerly Kellogg's). Sanket's academic detour, marked by a leisurely hostel life, resulted in a prolonged graduation. The narrative follows his decision to transition from preparing for bank exams to embracing the booming field of data science. His challenges and triumphs in securing roles at Cognizant and later Edelweiss Tokio Life Insurance shed light on the complexities of data engineering. The blog encapsulates Sanket's resilience, showcasing his commitment to continuous learning and eventual success in securing a coveted position at Kellogg's. 

Sanket Vishwakarma's path from a relaxed hostel lifestyle to achieving the position of a Data Engineer at Kellanova (formerly known as Kellogg's) was a captivating tale filled with surprising turns and unwavering decisions.

The following blog illustrates Sanket's journey, transitioning from a carefree lifestyle to becoming a data engineer at Kellogg's.

Backlogs Defeated: Sanket's Triumph as a Data Engineer at Kellogg's

Sanket and hostel's laid-back lifestyle

Sanket's academic voyage commenced at a Tier II university, where he pursued a BSc in mathematics. However, his path deviated when he found comfort in the hostel's laid-back lifestyle.

Despite his initial passion for mathematics, Sanket got entangled in the carefree ambience of hostel life. Sanket's lack of attendance in lecture halls and reliance on his friends' notes resulted in a gradual disengagement from his academic responsibilities.

Semester exams, once a priority, became mere afterthoughts as he found himself captivated by the hostel's vibrant social atmosphere. Late-night conversations and impromptu adventures became the norm, overshadowing the importance of attending classes and studying for exams.

Sanket had backlogs, too. This deviation extended his three-year graduation to five years. While his peers diligently pursued their degrees, Sanket was lost in the allure of hostel life, oblivious to the consequences this would have on his future.

Sanket's attempt to reclaim his career

After obtaining his degree, Sanket carried a heavy burden due to the extended duration of his graduation. Determined to make a positive change in his life, he decided to prepare for bank exams. Successfully passing the preliminary exams for SBI's P.O., Sanket found himself at a crossroads when it came time to write the mains. 

Uninterested in pursuing the bank exams or a career in banking, I yearned for a new direction but was uncertain about which path to choose. I even considered the job role of a lab assistant. I didn't know which career path to consider. After careful consideration, I discovered the growing demand for data science and boldly decided to pursue it as my new journey.

Sanket's data science journey

As the Covid-induced lockdown was gradually lifted, opportunities began to arise. Companies like Cognizant were actively recruiting, and Sanket decided to try his luck. He secured a testing role but never truly felt at ease from day one.

During the initial six months of the job, Sanket primarily underwent training. This gave him time to enhance his skills. During this period, the idea of pursuing data science started to take shape in his mind. It grew so strong that he had a strong urge to resign and prepare for a data science job role. But then he thought, 

I already had a 2-year education gap and 3 year of career gap before I joined Cognizant, so total of 5-year gap and now resigning in 6 months might not look very good on my profile.

So, Sanket had no choice but to enrol in a data science course and study while continuing his job. He enrolled in OdinSchool's data science course.

Sanket's toughest challenge

Sanket's primary challenge was with his resume. Due to the AI resume scanners, the keywords like B.Tech were not matching with his resume. Then the education gap of 2 years and career gap of 3 years was also one of the concerns. Due to these gaps and his degree instead of engineering background, his resume was not even being shortlisted for the interview. 

Fortunately, with the guidance and support of OdinSchool's placement team and expert advisors, Sanket was able to transform his profile into a showcase of his valuable skills and experiences rather than a reflection of setbacks and failures. They helped him to emphasize his technical expertise and soft skills, allowing his resume to shine brightly among the competition.

After successfully completing the data science course at OdinSchool, Sanket secured a position as a data engineer at Edelweiss Tokio Life Insurance.

Sanket's daily life as a data engineer 

I feel lucky to have had a lot of exposure as a data engineer fresher at Edelweiss Tokio Life Insurance.

I had to do many things at the same time. Talking to different clients, working on AWS, and dealing with the data science team for business logic, various Python scripts and new requirements were all part of my daily work.

Most of his tasks involved cleaning and processing data. It was challenging because users would call directly if they had any issues with data. This challenged him but helped to improve his problem-solving skills on the spot.

Since it is a service company, he had to work long hours, almost 16-18 hours a day. Even though it was tough, dealing with all these challenges has been a great learning experience. It helped him grow into who he is now. 

After immersing himself in data engineering for a year and a half, Sanket yearned to delve deeper into advanced technologies and broaden his knowledge. Sanket has successfully secured a coveted role as a data engineer at Kellanova (formerly known as Kellogg's), embarking on a new chapter of his professional journey.

Sanket's learnings as a data engineer

As Raza Ali too emphasized, the seamless data flow is crucial for data analysts' and scientists' success. Without the expertise of data engineers in exporting and organizing data, these roles would be unable to progress effectively.

  • Hence, to excel in data engineering, it is essential to master advanced SQL, going beyond just the basics. Know the workings of different databases like Snowflake, MongoDB, etc.

  • Similarly, a thorough understanding of Python and Pyspark is necessary to navigate the complexities of data manipulation.

  • Additionally, as most companies operate on cloud platforms, such as AWS, familiarity with cloud technologies is a must-have skill. Knowing machine language is also beneficial, as it helps you better understand a data scientist's requirements.

  • Finally, master any one data science technology but be aware of other technologies as well.

Sanket's inspiring interview about his data science journey

Sanket's journey from a relaxed hostel lifestyle to becoming a Data Engineer at Kellanova (formerly known as Kellogg's) is a testament to the power of perseverance and the ability to learn from past mistakes.

It serves as a reminder that setbacks can often pave the way for unexpected opportunities and that it's never too late to take control of one's destiny.

Frequently Asked Questions (FAQ) - Data Engineer

I have a non-IT background. Can I also become a data engineer?

Yes! A person with a non-IT background, like B.Sc, B.Com, etc., can become a data engineer. The best example would be that of Aman Verma who could start his career only as a tutor but now he is a data engineer. Though strong programming and analytical skills are required, they are not mandatory skills when entering the data science domain.

Can I become a data engineer in 6 months?

Yes, you can become a data engineer in 6 months, provided you thoroughly know all the industry requirements and the latest tools and technologies. This can be done easily upon enrolling in an industry-vetted data science program.

Is a Data Engineer in demand?

Data Engineering is in great demand because 2.5 quintillion bytes (2.5 followed by 18 zeros) of data is created each day, and this massive amount of data generated every day has to be evaluated, cleansed, processed, stored, and analyzed.

Only data engineers can create the right data process and its architecture.

Is Data Engineer a tough job?

To be honest, it can be challenging to become a data engineer. But after you've mastered the necessary abilities and secured your first role, you'll have lots of flexibility to mould your dream job. Rarely will you be told what tools to utilise; instead, you'll get to decide what to work on and when.

Again like, I said before, getting into the right role and the ability to use the right industry required tools, only an industry-vetted data science whose curriculum is regularly updated can help.

Is Data Engineer a well-paid job?

Yes, they do but their salaries depend on the experience they carry. As per the latest glassdoor numbers, the salary in India ranges between 10L to 27L per annum.

 

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