Verizon

A strict three-round, time-boxed loop expecting exact SQL (multi-join + optimization) and Hadoop/Spark fundamentals.

Cloud / platform

GCP/AWS + Hadoop on-prem; Hive, Spark

Reported difficulty

Not reported

SQLPythonDSAHadoopHiveSpark

Hiring process

Screening

Technical

Behavioral

Offer

Round-by-round breakdown

3

01

SQL

Medium confidence

Multi-table joins; query optimization for performance
Delivering data to ML pipelines and meeting SLAs

02

Python / DSA

Medium confidence

DSA + programming + SQL in the coding round

03

Hadoop / Spark

Medium confidence

Hadoop architecture; data ingestion processes
Hive, Spark

System & pipeline design prompts

1

Telecom usage/network pipeline (SLAs for ML pipelines)

Rejection patterns

3

Not delivering exact correct solutions within the time limit (strict format)
Weak SQL optimization
Shaky Hadoop/Spark

Reported experiences

1

Data Engineer

SQL Qs sharedFirst-hand

LinkedIn (Sachin Patil) shared Verizon DE SQL questions (multi-join + optimization), confirming the SQL-heavy, strict coding round.

Hiring process

Round-by-round breakdown

SQL

Python / DSA

Hadoop / Spark

System & pipeline design prompts

Prep — high priority

Prep — medium priority

Rejection patterns

Reported experiences

Data Engineer

Rehearse for Verizon

Verizon

Hiring process

Round-by-round breakdown

SQL

Python / DSA

Hadoop / Spark

System & pipeline design prompts

Prep — high priority

Prep — medium priority

Rejection patterns

Reported experiences

Data Engineer

Rehearse for Verizon