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πŸ“š A structured, day-by-day preparation tracker to become job-ready at TCS and interview-ready for future Data Engineering roles. Includes DSA with Java, Python scripting, SQL practice, and core CS concepts.

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πŸ’Ό Job-Ready Track – Day-wise Prep for TCS & Data Engineering Interviews

πŸ—‚οΈ Overview

This repo contains my daily learning journey with hands-on DSA, Python, SQL, and CS concepts, to become job-ready and interview-prepared.


πŸ“… Day-wise Progress

Day 1

βœ… Java DSA (3 problems), OS (Processes vs Threads), Python (filtering, grouping), SQL queries
🧠 Key concepts: boolean indexing (Python Pandas), memory sharing in threads, SQL grouping
πŸ“ Full Reflection


Day 2

βœ… Java DSA (Sliding Window), DBMS (Indexing), Python (Data Cleaning with Pandas), Basic SQL with indexing
🧠 Key concepts: indexing trade-offs, data cleaning for reliable analysis, SQL indexing
πŸ“ Full Reflection


Day 3

βœ… Java DSA (Two Pointers – 3 problems), CN (OSI Model), Python (CSV Handling with Pandas)
🧠 Key concepts: two pointers for sorted arrays/strings, OSI layers & responsibilities, filtering & exporting CSV data with Pandas
πŸ“ Full Reflection


Day 4

βœ… Java DSA (Two Pointers - Medium level Problem), OS (CPU Scheduling Algorithms)
🧠 Key concepts: Learned how two pointers work in a given array, things to take care while designing a CPU scheduling algorithm, different CPU scheduling algorithms.
πŸ“ Full Reflection


Day 5

βœ… Java DSA (Prefix Sum + Hash Map), OS (Paging vs Segmentation), Python (ETL with Pandas), SQL (Mini Data Mart Queries)
🧠 Key concepts: Subarray sum logic using prefix sum, address translation in memory management, data aggregation with pandas, handling CSV encoding and foreign key errors.
πŸ“ Full Reflection


Day 6

βœ… Java DSA (Sliding Window), DBMS (ACID, Transactions), Python (Customer Modeling), SQL (Business Queries)
🧠 Key concepts: Unique substring logic with HashSet, core DBMS properties, customer-wise profit modeling, and SQL joins with aggregations.
πŸ“ Full Reflection


Day 7

βœ… Java DSA (Top K Frequent, Group Anagrams), CN (TCP/UDP, 3-Way Handshake), Python (JSON Parsing), SQL (Window Functions)
🧠 Key Concepts: Frequency Map + Heap, Anagram Grouping, Protocol Differences, JSON extraction, SQL Ranking
πŸ“ Full Reflection


Day 8

βœ… Java DSA (Heap-based Frequency Sort), OS (Deadlocks & Prevention Strategies), Python (CSV to SQLite ETL), SQL (GROUP BY + HAVING)
🧠 Key concepts: PriorityQueue sorting logic, Coffman’s conditions, real-world deadlock examples, CSV schema validation, SQL group filtering
πŸ“ Full Reflection


Day 9

βœ… Java DSA (Bucket-based Frequency Sort), OS (Disk Scheduling Algorithms), Python (JSON to SQLite ETL), SQL (Subqueries, CASE, NULL Handling)
🧠 Key concepts: Bucket frequency grouping, FCFS/SSTF/SCAN/LOOK disk strategies, safe JSON-DB insertions, smart NULL-safe SQL conditions
πŸ“ Full Reflection


Day 10

βœ… Java DSA (Next Greater Element I), Core CS (CAP Theorem), Python (SQLite to CSV Exporter), SQL (JOIN + CASE + IFNULL)
🧠 Key concepts: Monotonic Stack + HashMap, distributed DB tradeoffs, exporting DB data via Python, SQL joins and classification logic
πŸ“ Full Reflection


πŸ› οΈ Technologies Practiced

Java, Python, SQL, Pandas, Git, Operating Systems, DBMS, Computer Networks.


Stay tuned for more days! πŸš€

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πŸ“š A structured, day-by-day preparation tracker to become job-ready at TCS and interview-ready for future Data Engineering roles. Includes DSA with Java, Python scripting, SQL practice, and core CS concepts.

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