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2021 was the toughest year - I failed interviews with Accenture, TCS, Infosys😓

In 2022, I turned those rejections and cracked Kantaro as a front-end dev😁

This was my whole career journey - I had my resume rejected, couldn’t clear interviews, and at times even lost hope but…

I kept my goal in my vision and picked up my preparation right from resume optimization

✔️ I chose a basic template with important sections like - Skills, Projects, Education, etc.

✔️ Described all my projects in detail and used quantifiable numbers to show impact.

✔️ Searched the JD for important keywords, and included them to ace the ATS scan.

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From Novice to Navigator: My Journey with Data Science

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🌟 My interview experience at Kantar🌟
Having completed 2+ years here, I thought of sharing it for the first time🙈

📍OA Round - I was asked MCQs on core CS topics like DBMS and OS along with DSA.

📍 Tech Interview - This round challenged me with medium-level DSA questions. I solved them both in the given time, considering the edge cases and following proper coding conventions.

📍 Behavioral Interview - It focused on soft skills like teamwork, leadership, and conflict resolution. There were many scenario-based questions, which I answered using the STAR framework.

📍 Cultural Fit - This round assessed my work ethic and alignment with Kantar’s values.

After facing rejection with Accenture, IBM, etc, I gave multiple mock interviews and took feedback. This helped me ace Kantar’s interview🎉

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Do you know what? They won’t stop at mock interviews; they will also train you on DSA, assist in resume optimization and project building along with providing referrals! So, do connect!✨

*Please like and comment if you found my journey*

How did I land a technical role in this competitive market? And right after my college.

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Cracked a good company? Congrats!
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Before Kantar, I faced 50+ rejections 😓
My inbox was filled with “We’re moving forward with another candidate” messages.

I struggled with both the technical and behavioral rounds.
Here’s what I did to improve:

➤ Consistent DSA practice: I dedicated 3 hours every day after work to practicing DSA.

➤ Focus on System Design: I regularly worked on UML diagrams and key concepts.

➤ Prepare for behavioral rounds: I created stories for common questions and researched company values.

Rejections can really drain your motivation. It was tough to keep going after repeated setbacks. So, if you want to avoid this or are struggling right now, try to get help.

You can book a free consultation call with a senior engineer here for free: https://lnkd.in/gHPsaQh2

They’ll create a customized roadmap tailored to your goals and help you stay motivated. From technical skills to behavioral strategies, they’ll ensure you’re fully prepared for your next opportunity. 🚀

All the best!🌟

*referral tips*

You've heard and seen plenty of tips on requesting referrals.
Let me share how I evaluate them as a Senior Programmer at Kantar 🔽

☑️ Match skills to the job: I focus on whether the candidate’s skills and experience align with the job requirements.

☑️ Check the referrer’s insights: Strong referrals come with specific examples and detailed insights about the candidate.

☑️ Culture fit: I also look at whether the candidate’s values and working style align with our team and company culture.

☑️ Growth potential: Enthusiasm for the role and signs of growth potential are great indicators of future success.

I appreciate it when candidates make it easy for their referrer by providing detailed resumes and clear project highlights. It shows preparation and respect for everyone's time.

Remember, while referrals are valuable, they're just one part of the job search process. If your skills are weak, any referral strategy won’t work.

If you’re struggling with this, then platforms like Preplaced can connect you with experienced SDEs.

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I have said it before, I will it say it again

SQL is going to make or break the game for you.

So here’s a list of SQL Advanced Topics for your technical interviews! 🔥

𝟭. 𝗖𝗼𝗺𝗽𝗹𝗲𝘅 𝗝𝗼𝗶𝗻𝘀 𝗮𝗻𝗱 𝗦𝘂𝗯𝗾𝘂𝗲𝗿𝗶𝗲𝘀:
- Join types (INNER, LEFT, RIGHT, FULL OUTER); and
- How to use Subqueries efficiently in SELECT statements, WHERE clauses, and FROM clauses.

𝟮. 𝗪𝗶𝗻𝗱𝗼𝘄 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
- ROW_NUMBER(), RANK(), DENSE_RANK(), NTILE(), LEAD(), LAG(), FIRST_VALUE(), LAST_VALUE(),
- Use of OVER() with PARTITION BY and ORDER BY clauses.

𝟯. 𝗖𝗼𝗺𝗺𝗼𝗻 𝗧𝗮𝗯𝗹𝗲 𝗘𝘅𝗽𝗿𝗲𝘀𝘀𝗶𝗼𝗻𝘀 (𝗖𝗧𝗘𝘀):
- Using WITH clause for creating temporary result sets that can be referred to within a SELECT, INSERT, UPDATE, or DELETE statement.

𝟰. 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝗚𝗿𝗼𝘂𝗽𝗶𝗻𝗴:
- SUM, AVG, COUNT, MIN, MAX) and GROUP BY,
- ROLLUP, CUBE, and GROUPING SETS for multi-level aggregation.

𝟱. 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀:
- Techniques like pivoting (converting rows to columns);
- Unpivoting (converting columns to rows);
- Handling JSON and XML data formats

𝟲. 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 𝗮𝗻𝗱 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗧𝘂𝗻𝗶𝗻𝗴:
- Understanding how indexes work;
- How to optimize queries for performance, including the use of EXPLAIN plans to analyze query performance.

𝟳. 𝗦𝘁𝗼𝗿𝗲𝗱 𝗣𝗿𝗼𝗰𝗲𝗱𝘂𝗿𝗲𝘀, 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀, 𝗮𝗻𝗱 𝗧𝗿𝗶𝗴𝗴𝗲𝗿𝘀:
- Creating and using stored procedures;
- Functions for repetitive tasks; and
- Triggers for automated data manipulation or integrity checks.

𝟴. 𝗗𝗮𝘁𝗮 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 (𝗗𝗗𝗟) 𝗮𝗻𝗱 𝗗𝗮𝘁𝗮 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 (𝗗𝗖𝗟):
- Advanced knowledge of schema design,
- Table creation and Modification statements;
- Role and permission management using GRANT and REVOKE.

𝟵. 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗧𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝘀:
- Understanding transaction control with COMMIT, ROLLBACK, and SAVEPOINT;

𝟭𝟬. 𝗤𝘂𝗲𝗿𝘆 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀:
- Techniques for writing efficient SQL queries, avoiding common pitfalls; and
- Adhering to best practices for readability and maintainability.

𝟭𝟭. 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 (𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗼𝗳 𝗱𝗮𝘁𝗮 𝘄𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘀):
- Star schema, snowflake schema, fact tables

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