ZoomyCoconut
ZoomyCoconut

Advice on interview preparation

Data engineers and data analyst out here, I want a genuine advice, how really you are preparing for the interview, be it python coding, framework development and all related stuffs, I develop etl using python script and don't have much experience with big data, wherever iam applying for DE roles pyspark was put in first.. so to start with existing skill set how you guys are actually preparing for interview ,

I have overall 5.11 years of experience with initial 2 years in support and 3 years into analytics and etl development revolving mainly into python, not a promax developer, but wish to be. I have built the dashboard with respective etl development and I was the only developer in my team so couldn't discuss with my teammate. Please advice

9d ago
Talking product sense with Ridhi
9 min AI interview5 questions
Round 1 by Grapevine
PeppyQuokka
PeppyQuokka

Check Ansh Lamba’s YT channel

PrancingNoodle
PrancingNoodle

Hey, with almost 6 years of experience mostly in Python ETL and analytics your situation is quite common for many aspiring data engineers Preparing for DE interviews especially where PySpark and big data are expected can feel overwhelming My advice is to start by strengthening your core Python skills and then gradually learn PySpark fundamentals through hands-on practice Use online resources like Databricks tutorials or courses on platforms like Coursera and Udemy Build small projects that showcase ETL pipelines with PySpark and try to understand distributed computing concepts Also brush up on SQL and data modeling basics Since you have dashboard experience highlight your ability to deliver end to end solutions and problem solving If possible, join peer groups or communities to discuss and learn collaboratively Remember interview prep is a mix of coding practice system design and domain knowledge So set a schedule balancing all three Feel free to join our data community for resources, mock interviews, and peer support https://chat.whatsapp.com/B6weknl7133BQXjPva0pgB

BouncyDonut
BouncyDonut
  1. Core Skills (Python + SQL) Master Python ETL optimizations (generators, multiprocessing) and advanced SQL (CTEs, window functions).

  2. PySpark (Must for DE Roles) Learn RDDs, DataFrames, and Spark SQL. Practice partitioning and UDFs.

  3. System Design Basics Understand scalable ETL pipelines and warehousing (Star Schema, partitioning).

  4. Mock Interviews & Projects Build an end-to-end pipeline (data → ETL → dashboard) to showcase skills.

Need help? Join our Data Engineering community for referrals, mock interviews, and PySpark guidance: https://chat.whatsapp.com/B6weknl7133BQXjPva0pgB

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