Interview Process Overview

The Expedia Senior Data Engineer interview process included:

→ Hiring Manager Screening

→ Technical Deep Dive (Spark and Big Data)

→ System Design (Streaming Pipeline)

→ Behavioral Round

Round 1 – Hiring Manager Screening (Elimination Round)

This round served as an initial filter and focused on understanding project experience and basic problem-solving skills.

Project Discussion

I walked through my recent projects, explaining what I built, why certain design choices were made, and how the systems performed at scale. The interviewer focused on ownership, impact, and decision-making.

SQL Question

Question asked: Find customers who purchased Product A and Product B, but not Product C.

This was a classic group-by and filtering problem that tested understanding of conditional aggregation and exclusion logic.

DSA Question

A string manipulation problem was asked to test basic algorithmic thinking and attention to edge cases. The problem was straightforward but required careful handling of boundary conditions.

This round reinforced the importance of knowing your own projects deeply and being comfortable explaining both the technical and business context.

Round 2 – Technical Deep Dive (Spark and Big Data)

This round went deep into core data engineering concepts and Spark internals.

Spark Debugging Scenario

Question asked: A Spark job is running significantly slower than expected. How would you debug and optimize it?

The discussion covered examining Spark UI, identifying shuffle-heavy stages, checking partition sizes, caching strategies, and evaluating join types.

Incremental Loading Question

Question asked: How would you design incremental loading for large datasets?

I discussed approaches using timestamps, hash-based comparison, and identifying changed records efficiently to avoid full table scans.

Large-Scale Data Design Question

Question asked: You have two tables with ten billion records each, and around five million records are updated daily. How would you design this pipeline?

The discussion included partitioning strategies, incremental processing, storage formats such as Parquet, and selecting appropriate partition columns to balance performance and scalability.

This round emphasized reasoning through scale rather than naming technologies.

Round 3 – System Design (Streaming Pipeline)

This was a forty-minute system design round focused entirely on real-time data processing.

System Design Question

Question asked: Design a complete real-time streaming data pipeline.

The discussion covered tool selection, ingestion, processing latency, retries, scalability, and downstream consumption.

Fault Tolerance and Recovery

Follow-up questions included:

→ How does checkpointing work in streaming systems?

→ How does it help with fault tolerance and recovery?

Additional topics included state management, handling backpressure, ensuring data freshness, and designing for failure scenarios.

Round 4 – Behavioral Round

The final round focused on team dynamics, conflict resolution, and decision-making.

Behavioral Questions

Question asked: Tell me about a time you disagreed with your manager.

Another question focused on handling situations with unclear ownership and navigating ambiguity within teams.

Answers were expected to follow a structured format, highlighting context, action taken, and outcomes.

Key Takeaways from the Expedia Interview

Deep understanding of personal projects is critical, especially the reasoning behind architectural decisions. Streaming concepts such as checkpointing, state management, and failure handling are heavily emphasized. Interviewers value structured thinking and practical trade-offs more than buzzwords. Problem-solving appears in every round, whether through SQL, Spark scenarios, or system design discussions.

Final Thoughts

The Expedia Senior Data Engineer interview process was comprehensive and practical, focusing on real-world data engineering challenges rather than theoretical knowledge alone. Candidates preparing for similar roles should focus on mastering their project experience, thinking through large-scale data problems step by step, and communicating their approach clearly under pressure.

If you want, I can next convert this into a round-wise preparation checklist, a short interview summary post, or standardize it into your final reusable interview experience template for future rewrites.