Crack any Data Integration Engineer Interviews | 100 In-Depth Questions (Python, SQL, ETL) | GyanVah
This is a complete 1.20-hour deep-dive interview preparation video for
Data Integration Engineer / Data Engineer / ETL Engineer roles.
In this video, I cover 100 real interview questions with clear, in-depth explanations — not shortcuts or notes, but answers you can actually speak confidently in
Data Engineer / ETL Engineer interviews
Python + SQL based data roles
CRM, HRMS, POS data integration jobs
Remote & global company interviews
💡 What you’ll learn
✔ End-to-end ETL concepts
✔ Python for real-world data pipelines
✔ Advanced SQL used in production
✔ Incremental loads, idempotency & failures
✔ CRM, HRMS, POS integration
✔ Data quality, validation & reconciliation
✔ Data warehousing (facts & dimensions)
✔ Behavioral & ownership interview questions
This is not a crash course.
This is a mentor-style explanation designed to make you interview-ready at a global level.
🎯 Who should watch?
Freshers preparing for data roles
Software engineers moving into data engineering
Professionals struggling in interviews
Anyone tired of shallow tutorials
⏱️ Video Length: 1 Hour 20 Minutes
Pause, revise, and come back anytime.
📌 CHAPTERS / TIMESTAMPS
🔹 Foundation (ETL, Python, SQL Basics)
00:12 – ETL Basics & Importance
02:15 – Why Python for Data Integration
03:51 – Processing Large CSV Files
05:14 – Idempotency in Pipelines
06:47 – Handling Missing Data
08:10 – Logging & Monitoring
09:26 – Failure Handling
10:40 – Data Validation
11:46 – WHERE vs HAVING
12:38 – Handling Duplicates
🔹 Intermediate (SQL, ETL Design)
13:42 – Primary vs Unique Key
14:56 – SQL Window Functions
15:58 – SQL Query Optimization
16:57 – CTE Explained
17:49 – Incremental Loading
18:45 – Full Load vs Incremental
19:31 – CRM, HRMS & POS Integration
20:24 – Schema Changes
21:04 – Source-to-Target Consistency
21:35 – Production-Ready Pipelines
🔹 Advanced (APIs & Data Quality)
22:12 – REST APIs
23:22 – API Pagination
24:25 – API Rate Limits
25:07 – Staging Layer
25:59 – Late-Arriving Data
26:43 – Backfills
27:28 – Raw vs Staging vs Curated
28:06 – Ingestion vs Transformation
28:37 – Schema Drift
29:06 – Restartable Pipelines
🔹 System Design & Scale
29:33 – Safe Deduplication
30:30 – MERGE vs INSERT/UPDATE
31:19 – Load Validation
32:00 – Slowly Changing Dimensions
32:46 – SCD in HRMS
33:27 – Pipeline Restartability
34:01 – Schema Drift (Prod)
34:37 – Configuration Management
35:03 – Data Security
35:32 – Pipeline Testing
🔹 Production, Reliability & Ownership
35:57 – API Versioning
36:54 – Webhooks vs Polling
37:47 – Batch vs Streaming
38:34 – Data Quality Checks
39:09 – Monitoring Pipelines
39:40 – Data Reconciliation
40:15 – Failure Prioritization
40:45 – Conflicting Requirements
41:15 – Common Mistakes
41:45 – Production-Ready Systems
🔹 Architecture, Expert & Behavioral
42:14 – End-to-End Architecture
43:38 – Scaling Pipelines
44:32 – High-Volume POS Data
45:24 – Pipeline Dependencies
46:02 – Out-of-Order Data
46:39 – Fact & Dimension Design
47:12 – Updating Fact Tables
47:38 – Partitioning
48:05 – Clustering
48:26 – Cost Optimization
48:52 – Idempotent Pipelines
50:06 – Partial Failures
51:04 – Secrets Management
51:53 – Pipeline Security
52:44 – Safe Deployments
53:26 – SLAs
54:09 – Data Corruption
54:47 – Schema Breaks
55:23 – Auditing & Lineage
55:54 – Pipeline Health
56:24 – Speed vs Accuracy
57:23 – Handling Pressure
58:17 – Explaining Trade-offs
59:04 – Improving Pipelines
59:45 – Good vs Great Engineer
01:00:19 – Trust in Data
01:00:51 – Wrong Numbers in Reports
01:01:35 – AI & Analytics Models
01:02:13 – Resolving Conflicts
01:02:51 – Maintainable Python
01:03:27 – Technical Debt
01:04:27 – Stakeholder Trust
01:05:19 – Data Issues
01:06:11 – PII Handling
01:07:00 – Worst Failures
01:07:53 – Fast Recovery
01:08:29 – Ambiguous Requirements
01:09:06 – Non-Tech Communication
01:09:37 – Task Prioritization
01:10:07 – Why Data Engineering
01:10:41 – Why Hire You
01:11:33 – Questions to Interviewer
01:12:09 – Handling Feedback
01:12:43 – Staying Updated
01:13:17 – First 30 Days
01:13:51 – Measuring Success
01:14:24 – Hardest Part
01:14:53 – Staying Calm
01:15:27 – Career Growth
01:15:51 – Final Thoughts
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