Data Analyst vs Data Engineer vs Data Scientist — Which Data Career Should YOU Choose in 2025 & 26?

Upskill for high-paying data careers with 100% job switch assistance 🚀

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Let’s be honest — searching ‘data jobs’ on LinkedIn is confusing.
Analyst. Engineer. Scientist.
Same word — data — but totally different roles, responsibilities, and salaries.

In this video, we break down all three roles step-by-step so you finally understand:
➡ Which one fits YOUR background
➡ Which role pays better
➡ Which skills each job actually requires
➡ And how these roles work together inside real companies like Netflix, Amazon & Swiggy

By the end, you’ll have complete clarity on which data path is right for you.

💡 Here’s what you’ll learn:

✅ Data Analyst vs Data Engineer vs Data Scientist — real differences
✅ Skills required for each role (SQL, Python, ML, Spark, Tableau & more)
✅ Salary comparison (India & global ranges)
✅ Which role suits beginners vs working professionals
✅ Real company examples — Netflix, Amazon, Swiggy
✅ How all 3 roles work together in real-world data teams
✅ Clear roadmap to choose the right career path

💼 Want a proven roadmap to transition into Data Engineering?

Meritshot’s Data Engineering Program helps you master real tools like Kafka, Spark, Airflow & Snowflake — with live projects, expert mentors, and job-switch assistance.

👉 Upskill with 100% Job Switch Assistance:

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⏱ Timestamps

00:00 – 00:35 — Why data careers feel confusing
00:35 – 00:57 — What modern companies really do with data
00:57 – 01:30 — Data Analyst explained — skills, salary, responsibilities
01:30 – 02:16 — Data Engineer explained — tools, pipelines, real salaries
02:16 – 02:50 — Data Scientist explained — ML, AI, use cases
02:50 – 04:18 — Analyst vs Engineer vs Scientist — simplified
04:18 – 04:55 — Real example: How Swiggy uses all 3 roles
04:55 – 05:13 — Final thoughts & next steps

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