Snyk India Data Engineer Interview: Rounds, Questions and Preparation

What the job involves

Data Engineers at global tech companies like Snyk build and maintain the data infrastructure that powers analytics, machine learning, and internal reporting. Day to day, they design ETL pipelines, manage data warehouses, ensure data quality, and collaborate with analysts and product teams to make data reliable and accessible. Freshers typically start by writing SQL, building batch or streaming pipelines, and learning cloud data tools.

Role and Technical Knowledge

1. 1

   Explain the difference between ETL and ELT, and when you would use each.

   Mention that ETL transforms before loading while ELT loads raw data first and transforms in the warehouse. Give examples like using ELT with cloud warehouses such as Snowflake or BigQuery.

2. 2

   What is a slowly changing dimension (SCD) and how would you handle a Type 2 change?

   Describe Type 2 as keeping history with new rows and effective dates. Show you can design a dimension table with surrogate keys and current flag columns.

3. 3

   Write a SQL query to find the second highest salary from an employee table.

   Use a subquery with MAX or a window function like DENSE_RANK. Explain the logic and mention handling ties or nulls.

4. 4

   What are the key differences between a data lake and a data warehouse?

   Cover schema-on-read vs schema-on-write, storage cost, and typical use cases. Mention that modern lakehouse architectures combine both.

Practical Scenarios and Problem Solving

1. 5

   You notice that a daily pipeline has been failing for three days. How would you debug and fix it?

   Walk through checking logs, identifying the failure point, validating upstream data, testing fixes in a staging environment, and adding monitoring to prevent recurrence.

2. 6

   How would you design a pipeline to ingest clickstream data from a web application into a data warehouse?

   Mention streaming or batch ingestion, using tools like Kafka or Kinesis, landing data in a data lake, then transforming and loading into the warehouse. Discuss partitioning and late-arriving data.

3. 7

   A stakeholder reports that a dashboard shows incorrect numbers. How do you investigate?

   Start by checking the dashboard query, then trace back to source tables, validate joins and filters, and compare with raw data. Communicate findings clearly and document the root cause.

4. 8

   How would you optimize a slow-running SQL query on a large table?

   Discuss indexing, partitioning, avoiding SELECT *, using EXPLAIN plans, and filtering early. Mention that sometimes denormalization or pre-aggregation helps.

Behavioural and Teamwork

1. 9

   Tell me about a time you had to learn a new technology quickly for a project.

   Use the STAR method. Highlight your learning approach, resources used, and how you applied it to deliver results.

2. 10

   Describe a situation where you disagreed with a teammate on a technical approach. How did you handle it?

   Show that you listen, present data or trade-offs, and focus on the best outcome for the project. Avoid sounding rigid or dismissive.

3. 11

   Give an example of a time you made a mistake in a project and how you fixed it.

   Be honest about the mistake, emphasize ownership, the corrective action, and what you learned to prevent it in future.

HR and Career Motivation

1. 12

   Why do you want to work as a Data Engineer at a global tech company like Snyk?

   Connect your interest in data infrastructure to the company's data-driven products. Show you understand the scale and impact of data engineering in security or developer tools.

2. 13

   Where do you see yourself in three years as a Data Engineer?

   Express a desire to deepen technical skills in cloud data platforms and take ownership of pipelines. Mention interest in mentoring or leading small projects.

3. 14

   How do you keep your data engineering skills up to date?

   Mention following blogs, taking courses, working on personal projects, and contributing to open source. Show genuine curiosity.