Interview questions
Preparing for a data engineering interview at TCS? This page contains 13 real interview questions sourced from verified TCS interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
TCS data engineering interviews typically focus on Spark/Big Data, SQL, and Behavioral. The interview bar skews toward harder problems (6 hard vs. 5 easy), suggesting emphasis on depth and system-level thinking.
Use the difficulty filters above to focus your preparation. For each question, attempt your own answer first, then compare with our expert solution. You can also practice these questions in our AI Mock Interview Coach for real-time feedback.
Design a fault-tolerant Spark Streaming checkpoint strategy: what to persist, recovery semantics, and cost/scalability trade-offs with checkpoint frequency.
How do you handle version conflicts for libraries?
What are the differences between %run and dbutils.notebook.run?
How do you install a Python library that is not in the Databricks runtime?
What factors determine the optimal number of partitions for a large file?
What is dynamic partition pruning, and how does it optimize query execution?
Explain Delta Live Tables and their features, such as declarative pipeline definition and automatic data validation.
Explain data encryption in Databricks, both at rest and in transit.
Explain the architecture of Databricks, including the control plane and data plane.
How does Auto Loader avoid reloading files with the same name?
How does Databricks integrate with external storage systems?
What are the differences between %pip and %conda commands in Databricks?
What are the performance considerations when using Auto Loader?
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