Google BigQuery
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Google’s love letter to SQL fans who hate waiting. A serverless, fully-managed data warehouse, BigQuery excels at handling massive datasets without breaking a sweat—or requiring you to think about infrastructure. Its pay-as-you-go pricing model is straightforward enough to make Redshift sweat, and its seamless integration with the Google ecosystem (hello, Sheets and Looker) is a big plus.
But here’s the catch: it’s great for queries, not for transactions. Updates and deletes? Painfully slow. Complex transformations? Better off in a dedicated ETL tool. And while its flat-rate pricing option is tempting for high-volume users, the cost can balloon if you’re not diligent with query optimization or data partitioning.
Best suited for analytics-first shops with structured data and a love of SQL, BigQuery delivers on speed and simplicity—just don’t bring it to a transaction-heavy brawl.
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Jobs in using Google BigQuery for but please no
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data engineer
Senior Data Engineer @ sensorfact
NL | 2025-12-25
Sensorfact’s Senior Data Engineer role reads like a battle plan for industrial IoT data: build real-time streams from raw sensor data, detect faults on the fly, and serve personalised guidance via...
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AWS Glue, Analytics, AI/ML, MLOps, Cloud Computing, AWS, Kafka, Flink, ClickHouse, Prefect, AWS Lambda, API, Agile/Scrum, IoT, PhD, Computer Science, Python, Data Streaming, Spark, Kubernetes, Docker, Scala, Airflow, Git, CI/CD, PostgreSQL, Redshift, BigQuery |
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