If you are learning Data Engineering and feel confused about:
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What to study next
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Whether you are ready for interviews
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Why progress feels slow
You are not alone.
Most learners don’t fail because they lack ability.
They fail because they lack a clear plan.
This 90-day roadmap is designed to remove confusion and create structured progress.
📅 Phase 1 (Days 1–30): Build Strong Foundations
Your goal in the first 30 days is clarity — not speed.
✅ Focus Areas:
1️⃣ SQL Mastery (Non-Negotiable)
Practice daily:
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Joins
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Group By & Aggregations
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Subqueries
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Window functions
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Data cleaning scenarios
SQL is asked in almost every interview.
2️⃣ Understand Data Flow
Learn how data moves:
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Source systems
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ETL process
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Data warehouse
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Reporting layer
You must understand this pipeline clearly.
3️⃣ Basic Python for Data Handling
Focus on:
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Reading files
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Data transformation logic
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Simple automation scripts
Don’t aim for perfection — aim for usability.
📅 Phase 2 (Days 31–60): Learn Real Processing Tools
Now move to practical tools.
✅ Focus Areas:
1️⃣ Apache Spark Basics
Understand:
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Transformations vs actions
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Partitioning
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Lazy evaluation
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Basic optimization
Always ask: Why is this useful in big data?
2️⃣ Data Pipeline Thinking
Build a simple pipeline:
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Ingest CSV data
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Clean it
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Store in database
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Query results
This gives practical confidence.
3️⃣ Cloud Basics (AWS/Azure/GCP)
Learn:
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Storage services
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Compute services
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Basic data processing setup
Companies expect cloud awareness.
📅 Phase 3 (Days 61–90): Industry-Level Thinking
This is where you become job-ready.
✅ Focus Areas:
1️⃣ Performance Optimization
Learn:
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How to reduce shuffle in Spark
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Indexing in databases
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Partition strategies
Interviewers love performance discussions.
2️⃣ Error Handling & Monitoring
Ask yourself:
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What if pipeline fails?
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How will alerts work?
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How to log issues?
This mindset separates beginners from professionals.
3️⃣ Mock Interviews
Start practicing:
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SQL questions
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Scenario-based questions
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System design basics
Speak answers out loud.
Communication matters.
🔥 The Biggest Shift You Must Make
Stop asking:
“What tool should I learn next?”
Start asking:
“What problem am I trying to solve?”
Companies hire problem-solvers — not tool collectors.
📈 How You Know You Are Job-Ready
You are ready when you can confidently explain:
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How data flows in a company
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How performance issues happen
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How to debug failures
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Why one architecture is better than another
Not when you finish 10 courses.
🎯 Final Thought
Consistency beats intensity.
Even 2–3 focused hours daily for 90 days can completely transform your confidence and interview readiness.
Clarity + Practice + System Thinking = Job Offers.
👨💻 About the Author
Ritesh shares practical insights on Data Engineering, interview preparation, and real-world technology learning strategies to help professionals become industry-ready.
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