Interview questions
Preparing for a data engineering interview at Lumiq? This page contains 12 real interview questions sourced from verified Lumiq interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
Lumiq data engineering interviews typically focus on SQL, General/Other, and Spark/Big Data. The interview bar skews toward harder problems (7 hard vs. 2 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.
Explain the differences between a Data Lake and a Data Warehouse.
Explain your cloud-based data pipeline on AWS
Data Security in BFSI - encryption, IAM, auditing
Data Storage and Retrieval Optimization techniques
Spark Coding: Using explode() Function to flatten nested arrays
Data Modeling and Airflow Scheduling - star schema, cron, backfill
Designing scalable data models - explain approach
Kafka Basics - architecture, topics, partitions, producers, consumers, Zookeeper
Query Performance in Redshift - optimization
SQL Problem - multiple table joins and window functions
Data-Related Issues Encountered - handling skewed data
Spark Optimization - broadcast joins, caching, coalescing, predicate pushdown, AQE
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