Databricks

big data, analytics, spark
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Spark on steroids, with a side of notebooks. Touted as the go-to platform for unified analytics, Databricks brings managed Spark clusters, collaborative notebooks, and seamless integration with cloud storage under one (expensive) roof. If you’re wrangling massive datasets or running complex ML workflows, it’s a powerful choice—especially for distributed computing without sweating over cluster management.
But let’s not ignore the elephant in the room: Databricks is a jack-of-all-trades but master of none. Its notebooks are decent, though hardly revolutionary. Its SQL features lag behind dedicated warehouses like Snowflake, and costs can escalate quickly if you’re careless with cluster sizing or fail to shut things down.
Ideal for hybrid teams juggling data engineering and data science, but for pure analytics or lightweight ETL? Consider simpler, cheaper alternatives. A brilliant tool if your problems fit its paradigm—just don’t expect it to be your one-size-fits-all solution.

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Jobs in using Databricks for but please no

analytics engineer

Engineering Lead - Data @ hub-24

AU | 2025-12-26
This role seeks a passionate, collaborative data engineering lead who thrives in innovation and team collaboration. The candidate should possess deep technical expertise in modern data platforms,... read more »
Data Engineering, Data Governance, Computer Science, Python, Databricks, dbt, Fivetran, Power BI, Data Modelling, Git, CI/CD, Agile/Scrum
analytics engineer

Solution Architect @ hub-24

AU | 2025-12-26
Hub24 seeks a Data Solution Architect to own the blueprint of its data platform, bridging business and tech with a mix of hands-on rigor and leadership. The role demands enterprise-grade data... read more »
Management, Agile/Scrum, Analytics, Computer Science, Python, Databricks, dbt, Fivetran, Data Modelling, Git, CI/CD, Data Governance