๐ ๐ ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐ ๐๐ฎ๐๐ฎ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ฆ๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒ (โ 6 ๐ฅ๐ผ๐๐ป๐ฑ๐)
Here are the stages I went through, plus what I gathered from others online:
โธป
๐ญ. ๐ฅ๐ฒ๐๐๐บ๐ฒ ๐ฆ๐ต๐ผ๐ฟ๐๐น๐ถ๐๐๐ถ๐ป๐ด / ๐ฅ๐ฒ๐ฐ๐ฟ๐๐ถ๐๐ฒ๐ฟ ๐ฆ๐ฐ๐ฟ๐ฒ๐ฒ๐ป
The recruiter reviews your resume to check alignment with technical skills (SQL, data pipelines, cloud tools like Azure, Spark etc.) and project experience.
They may also ask about your background, motivation, and career goals. Strong communication and a clear resume really help.
๐ฎ. ๐ง๐๐ผ ๐ง๐ฒ๐ฐ๐ต๐ป๐ถ๐ฐ๐ฎ๐น ๐ฅ๐ผ๐๐ป๐ฑ๐ (1 Hour Each)
These rounds dive deep into technical expertise. Common topics:
โข SQL performance & optimization
โข Data modelling
โข Pipeline & ETL design
โข Handling edge cases
โข Cloud services (Azure Data Factory, Databricks, Synapse)
โข DSA questions on Arrays & Linked Lists, Queue
One round may involve system/architecture design (e.g., scalable data warehouse, streaming pipeline). Another may focus on coding or troubleshooting data pipelines.
โธป
๐ฏ. ๐๐ถ๐ฟ๐ถ๐ป๐ด ๐ ๐ฎ๐ป๐ฎ๐ด๐ฒ๐ฟ ๐ฅ๐ผ๐๐ป๐ฑ
This round mixes technical and behavioural aspects. The manager checks for:
โข Problem-solving ability
โข Ownership
โข Stakeholder management
๐ฐ. ๐๐ (๐๐ ๐๐ฝ๐ฝ๐ฟ๐ผ๐ฝ๐ฟ๐ถ๐ฎ๐๐ฒ) / ๐ ๐ฎ๐ป๐ฎ๐ด๐ฒ๐ฟ๐ถ๐ฎ๐น ๐ฅ๐ผ๐๐ป๐ฑ
A senior-level evaluation focusing on leadership, collaboration, and cultural fit.
You may face behavioural questions about handling ambiguity, conflict, mentoring, and driving impact across teams.
They may also ask how you ensure scalability, quality, and reliability in data systems.
๐ฑ. ๐๐ฅ ๐ฅ๐ผ๐๐ป๐ฑ: ๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ & ๐ข๐ณ๐ณ๐ฒ๐ฟ ๐๐ถ๐๐ฐ๐๐๐๐ถ๐ผ๐ป
Covers compensation (base, bonus, stocks), benefits, role level, and formalities like relocation or background checks.
Post #1103
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