Databricks
Unified analytics platform built on Apache Spark for data engineering and ML.
4 Rounds
~21 Days
Hard
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Data Engineer
•
Behavioral
•
medium
Databricks highly values 'Customer Obsession'. Tell me about a time you had to pivot a data engineering project completely because the customer's requirements or business needs changed.
#Customer Obsession
#Adaptability
#Communication
#Agile
Data Engineer
•
Behavioral
•
medium
Tell me about a time you identified a major bottleneck in a legacy data pipeline. How did you convince your team to adopt your proposed architectural changes?
#Influence
#Problem Solving
#Initiative
#Mentorship
Data Engineer
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Coding
•
medium
Given a list of user session logs with start and end timestamps, write a Python function to find the peak concurrent active users.
#Python
#Intervals
#Sorting
#Time Complexity
Data Engineer
•
Coding
•
hard
Write a SQL query to identify 'sessionization' of user clicks. A new session starts if there is a gap of more than 30 minutes between clicks for a given user.
#Window Functions
#Sessionization
#CTEs
#LAG/LEAD
Data Engineer
•
Coding
•
medium
Write a Python script to flatten a deeply nested JSON object representing e-commerce transactions into a tabular format suitable for a Pandas or Spark DataFrame.
#Python
#Recursion
#Data Parsing
#JSON
Data Engineer
•
Coding
•
medium
Given a table of employee salaries and departments, write a SQL query to find the top 3 highest paid employees in each department without using the LIMIT clause.
#Window Functions
#Ranking
#Aggregations
Data Engineer
•
System Design
•
hard
Design a real-time analytics platform for IoT telemetry data using Databricks. Walk through the ingestion, processing, and serving layers using the Medallion architecture.
#Streaming
#Medallion Architecture
#Kafka
#Structured Streaming
#Delta Live Tables
Data Engineer
•
System Design
•
medium
How would you handle late-arriving data and out-of-order events in a Spark Structured Streaming pipeline? Explain the concept of watermarking.
#Structured Streaming
#Watermarking
#Late Data
#Event Time
Data Engineer
•
System Design
•
hard
Design a batch ETL pipeline to process 10TB of daily log data. The business needs to query this data interactively with sub-second latency. How do you model the data and optimize the storage?
#Batch Processing
#Data Modeling
#Performance Optimization
#Lakehouse
Data Engineer
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Technical
•
hard
You have a Spark job joining a massive fact table with a dimension table, and it is failing with an OutOfMemory (OOM) error due to data skew. How do you diagnose and fix this?
#Data Skew
#OOM
#Salting
#AQE
#Broadcast Joins
Data Engineer
•
Technical
•
medium
Explain how Delta Lake implements ACID transactions on top of cloud object storage. How do the transaction log and checkpointing work?
#Delta Lake
#ACID
#Parquet
#Transaction Log
#Concurrency
Data Engineer
•
Technical
•
medium
What is Adaptive Query Execution (AQE) in Spark 3.x? Explain the three main features it introduces and how they improve query performance.
#AQE
#Performance Tuning
#Query Plans
#Shuffle Partitions
Data Engineer
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Technical
•
medium
Compare and contrast Z-Ordering and standard partitioning in Delta Lake. When would you use one over the other?
#Z-Ordering
#Partitioning
#Data Skipping
#Delta Lake
Data Engineer
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Technical
•
hard
Walk me through the exact execution lifecycle of a Spark application from the moment you submit it using spark-submit to the final output. Mention the Driver, Executors, Tasks, and Stages.
#Distributed Systems
#DAG
#Task Scheduling
#Cluster Manager
Data Engineer
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Technical
•
medium
How do you handle schema evolution in a continuous ETL pipeline writing to Delta Lake? What happens if an upstream source drops a column or changes a data type?
#Schema Evolution
#Data Quality
#ETL
#Delta Lake
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Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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Always explain your thought process before writing code or drawing architecture.