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 Scientist
•
Behavioral
•
medium
Databricks moves very fast. Tell me about a time you had to deliver an ML model or analysis under a very tight deadline with ambiguous requirements.
#Ambiguity
#Delivery
#Prioritization
#Bias for Action
Data Scientist
•
Behavioral
•
easy
Tell me about a time you discovered a significant flaw in your data or model after it was already shared with stakeholders. How did you handle it?
#Integrity
#Communication
#Problem Solving
#Ownership
Data Scientist
•
Coding
•
medium
Write a PySpark script to calculate the 7-day rolling average of cluster compute costs per customer, given a massive dataframe of daily billing events.
#PySpark
#Window Functions
#Distributed Computing
Data Scientist
•
Coding
•
medium
Given a table of `job_runs` (job_id, workspace_id, start_time, end_time, status), write a SQL query to find the workspace with the highest rate of failed jobs in the last 7 days, considering only workspaces with at least 100 runs.
#SQL
#Aggregations
#CTEs
#Filtering
Data Scientist
•
Coding
•
medium
Given a list of strings representing Databricks notebook execution logs, write a Python function to extract the most frequent error codes and return them sorted by frequency. Assume logs are unstructured text.
#Python
#String Parsing
#Hash Maps
#Regex
Data Scientist
•
Coding
•
hard
Given a table of `user_logins` (user_id, login_timestamp), write a SQL query to find the maximum number of consecutive days each user has logged into the Databricks platform.
#SQL
#Window Functions
#Gaps and Islands
Data Scientist
•
Coding
•
hard
Write a Python algorithm to implement a stratified sampling method for a dataset that is too large to fit into memory, reading it chunk by chunk.
#Python
#Streaming
#Reservoir Sampling
#Memory Management
Data Scientist
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System Design
•
hard
Design a machine learning system to predict which Databricks customers are likely to churn in the next 30 days. Discuss feature engineering, model selection, and how you would scale the inference using Delta Lake.
#Churn Prediction
#Delta Lake
#Scalability
#Feature Engineering
Data Scientist
•
System Design
•
hard
Design an LLM-powered coding assistant for Databricks notebooks (similar to Databricks Assistant). Focus on the telemetry data you would collect to evaluate the model's performance offline and online.
#LLMs
#Telemetry
#Online Evaluation
#Product Analytics
Data Scientist
•
Technical
•
hard
Explain how Apache Spark handles out-of-memory (OOM) errors during a wide transformation. How would you diagnose and fix an OOM error in a PySpark ML pipeline?
#Apache Spark
#OOM
#Debugging
#Distributed ML
Data Scientist
•
Technical
•
medium
How does Delta Lake handle ACID transactions under the hood? Explain how you would use time travel to recover a dropped ML feature table.
#Delta Lake
#ACID
#Time Travel
#Storage
Data Scientist
•
Technical
•
hard
You are training a distributed XGBoost model on a massive dataset using Spark. The training job is taking too long and some executors are idling. How do you identify the bottleneck and optimize the training process?
#Distributed ML
#XGBoost
#Spark
#Performance Tuning
Data Scientist
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Technical
•
medium
We want to test a new auto-scaling algorithm for Databricks SQL warehouses. How would you design the A/B test? What are your primary and secondary metrics?
#A/B Testing
#Experimentation
#Metrics
#Cloud Infrastructure
Data Scientist
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Technical
•
medium
Explain the difference between a broadcast hash join and a sort-merge join in Spark. When would you force a broadcast join in a data science pipeline?
#Spark Joins
#Optimization
#Big Data
#Query Planning
Data Scientist
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Technical
•
medium
How would you use MLflow to manage the lifecycle of a model that requires frequent retraining? Describe the architecture of your CI/CD pipeline for this model.
#MLflow
#Model Registry
#CI/CD
#Model Lifecycle
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Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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