SQL & Data Modeling
Writing non-trivial SQL queries
Designing schemas for analytical workloads
Normalization vs denormalization
Partitioning, clustering, indexing
Coding & Algorithms
Implementing basic data transformations using Python or Java
Manipulating arrays, strings, hash maps
Focus on clean, efficient code — not LeetCode “hard” algorithms, but solid reasoning
Data Engineering Concepts
ETL pipeline design: source → transformation → sink
Handling late-arriving data, deduplication, error handling
Batch vs streaming tradeoffs
Familiarity with GCP tools like Dataflow, Pub/Sub, BigQuery (if mentioned in resume)