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What technologies are you most comfortable with?

SQLhard0.5 min readPremium
Frequency
Low
Asked at 1 company
Category
487
questions in SQL
Difficulty Split
130E|271M|86H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Fragma Data Systems
Key Concepts Tested
airflowbigquerylakehousepythonsnowflakesparksql
Expert AnswerPremium
95 wordsInterview-ready
**Situation**: As a senior data engineer, I've worked across SQL, Spark, orchestration, and cloud. **Task**: Deliver reliable pipelines that scale. **Action**: Core stack: SQL (Snowflake, BigQuery, Spark SQL), Python, Spark/PySpark, dbt, Airflow/Prefect, cloud (AWS/GCP). Production experience: streaming (Kafka), lakehouse (Delta), ML pipelines. I focus on fundamentals—modeling, testing, observability—that transfer across tools....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Fragma Data Systems. The answer also includes follow-up discussion points that interviewers commonly explore.

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