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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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data engineer

Cloud & AI Platforms, Senior Data Solution Engineer (大手のお客様向けプリセールス エンジニア) @ microsoft

JP | 2025-12-24
This role involves guiding enterprise clients through secure, scalable cloud database and analytics solutions, with a notable focus on Azure datastores and analytics portfolios. It offers a unique... read more »
Analytics, AI/ML, Cloud Computing, Microsoft, Azure, Fabric, BI, Databricks, Data Governance, SQL, Cosmos, PostgreSQL, Teradata, Netezza, Hadoop, Computer Science, BigQuery, Redshift, Snowflake, DWH, Data Lake, Big Data, Cyber Security, Management, Oracle, Synapse
data engineer

Data Solution Engineer @ microsoft

JP | 2025-12-24
This role involves guiding clients through the modernization of their data platforms using Azure Databases and Analytics, with a notable focus on customer engagement through proofs of concept and... read more »
AI/ML, Microsoft, Cloud Computing, Analytics, Fabric, BI, Databricks, Data Governance, Azure, SQL, Cosmos, PostgreSQL, Teradata, Netezza, Hadoop, BigQuery, Redshift, Snowflake, DWH, Data Lake, Big Data, Cyber Security, Management, Oracle, Synapse