Why Faridabad Students Are Choosing Data Engineering in 2026

Phase 1 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review the day's learning goals
9:00 AM — Live class / recorded lecture (2 hours)
   - Week 1: SQL fundamentals
   - Week 2: Python for data
   - Week 3: Linux & Git
   - Week 4: Data modelling
12:00 PM — Lunch break
1:00 PM — Hands-on practice (2 hours)
   - Solve SQL problems, write Python scripts, model schemas
3:00 PM — Mentor check-in / doubt session (30 min)
4:00 PM — Assignment work (1 hour)
5:00 PM — Review notes, plan tomorrow
6:00 PM — Break / exercise
8:00 PM — Read data blogs (30 min)
10:00 PM — Wind down

Week 1 Review:
□ Can I write complex SQL JOINs?
□ Do I understand GROUP BY and subqueries?
□ Have I solved 30 SQL problems?

Week 2 Review:
□ Can I read and clean data with Pandas?
□ Have I called an API from Python?
□ Have I built a small data script?

Week 3 Review:
□ Am I comfortable with Linux commands?
□ Can I schedule a job with cron?
□ Do I know the Git workflow?

Week 4 Review:
□ Do I understand normalisation?
□ Can I design a star schema?
□ Have I built an ER diagram?

Phase 2 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review the day's learning goals
9:00 AM — Live class / recorded lecture (2 hours)
   - Week 5: Apache Spark
   - Week 6: Airflow orchestration
   - Week 7: Cloud warehouses
   - Week 8: End-to-end pipeline
12:00 PM — Lunch break
1:00 PM — Hands-on practice (2 hours)
   - Write Spark jobs, build DAGs, load data into warehouses
3:00 PM — Mentor check-in / doubt session (30 min)
4:00 PM — Assignment work (1 hour)
5:00 PM — Review notes, plan tomorrow
6:00 PM — Break / exercise
8:00 PM — Read data blogs (30 min)
10:00 PM — Wind down

Week 5 Review:
□ Can I write Spark DataFrame transformations?
□ Have I processed a large dataset?
□ Do I understand partitioning?

Week 6 Review:
□ Have I built an Airflow DAG?
□ Do I understand scheduling and retries?
□ Have I added monitoring?

Week 7 Review:
□ Have I loaded data into Redshift/BigQuery/Snowflake?
□ Do I understand schema design?
□ Can I query data from the warehouse?

Week 8 Review:
□ Is my end-to-end pipeline complete?
□ Is it documented?
□ Is it on GitHub?

Phase 3 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review the day's learning goals
9:00 AM — Portfolio / interview prep (2 hours)
   - Week 9: Portfolio & case studies
   - Week 10: Mock interviews
   - Week 11: Placement drives
   - Week 12: Evaluate offers
12:00 PM — Lunch break
1:00 PM — Applications & follow-ups (2 hours)
3:00 PM — Mentor check-in / feedback (30 min)
4:00 PM — Interview practice (1 hour)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Break / exercise
8:00 PM — Practice interview questions (30 min)
10:00 PM — Wind down

Week 9 Review:
□ Have I published 2 projects?
□ Are they documented with problem, solution, results?
□ Are they on GitHub with READMEs?

Week 10 Review:
□ Have I done 5 mock interviews?
□ Can I write SQL under time pressure?
□ Can I explain my pipelines clearly?

Week 11 Review:
□ Have I attended 3+ placement drives?
□ Have I sent follow-ups?
□ Have I practiced more?

Week 12 Review:
□ Have I evaluated offers?
□ Have I negotiated?
□ Have I accepted a role?

Pipeline Design Template:

Pipeline name: _______________________________
Source: _____________________________________
Destination: ________________________________
Orchestrator: ☐ Airflow ☐ Dagster ☐ Other
Transformations:
1. 
2. 
3. 

Schema changes: _____________________________
Data quality checks: ________________________
Monitoring: ________________________________
SLA: _______________________________________

Documentation:
☐ Architecture diagram
☐ Code on GitHub
☐ Runbook / README

Weekly Learning Tracker:

Week: _____
Topics covered:
1. 
2. 
3. 

Hours spent: _____
Hands-on practice: _____
Assignments completed: _____

What I learned:
1. 
2. 

What needs more practice:
1. 
2. 

Next week's focus:
_______________________________

Interview Prep Tracker:

Company: _______________________________
Role: __________________________________
Interview date: _________________________

Topics to revise:
☐ SQL (JOINs, window functions)
☐ Python (Pandas, OOP)
☐ Spark / Airflow
☐ Cloud warehouses
☐ System design

Mock interview score: ____ / 10
Feedback:
_______________________________

Follow-up sent: ☐ Yes ☐ No