Data Engineer
Interview Date
October 2, 2024
Result
Not Specified
Difficulty
Medium-Hard
Rounds
3 rounds
Drive Type
Full-Time
Topics asked
Detailed experience
College: Not Specified
Interview Date: October 2, 2024
Interview Type: Full-Time
Result: Not Specified
Difficulty: Medium-Hard
Rounds: 3 rounds
Topics Asked: Previous Projects, Data Lineage (Spark), Spark Optimization, Snowflake Change Data Capture (CDC), Snowflake Internal Staging, Integration with External Data Sources (S3, GCS, Blob), SQL, Python, Big Data Concepts, Database Concepts, Data Warehousing, API Calling with Airflow, ETL using Airflow.
This interview experience for a Data Engineer role at Snowflake was shared on Medium. The candidate received a referral on LinkedIn. The recruitment process consisted of three main rounds.
Round 1: Preliminary Round (Screening) - 30 minutes
This round was conducted by the hiring manager. Questions focused on the candidate's previous projects, specifically how they used Databricks & API and worked on Snowflake Pipe for integration. Scenario-based questions were asked, such as how to capture data lineage for Spark code (explained using Datahub). Questions also covered Spark optimization, Snowflake Change Data Capture, Snowflake internal staging use cases, and how to integrate Snowflake with external data sources like S3, GCS, or Blob storage in different cloud services. The hiring manager then outlined that the next technical round would cover SQL, Python, Big Data concepts, Databases, Data Warehousing, and Spark optimization.
Round 2: Technical Interview (SQL/Python/Big Data Concepts/Database) - 1 hour 30 minutes
This round was conducted by a senior or staff data engineer. It covered a mix of SQL, Python coding, and concepts related to Big Data and Databases. Specific questions included SQL queries on an 'Employee' table (e.g., finding the Nth highest salary or employees who earn more than their managers). There were also questions on API calling with Airflow and how to capture changes if new records are inserted into source tables, and how Snowflake would capture these records and run an ETL job using Airflow.
Round 3: Hiring Manager Round - 45 minutes
This round involved behavioral questions combined with some technical aspects. Discussions revolved around projects involving Databricks, Spring Boot, JPA, and Hibernate. Questions were asked about challenges faced while converting requirements into solutions.