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

Senior Analytics Engineer @ rockstar-games

GB | 2025-12-23
Rockstar Games is recruiting a Senior Analytics Engineer to design and operate the data plumbing that underpins its mega-franchised games from a London studio. The role blends software development... read more »
Analytics, Big Data, AI/ML, Data Engineering, Data Quality, Git, CI/CD, Terraform, GitHub, Analytics Engineering, Databricks, Azure, Cloud Computing, Airflow, Astronomer, Computer Science, Python, PySpark, SQL, Agile/Scrum, Management, Data Streaming
analytics engineer

Data and Application Engineer @ primus-connect

GB | 2025-12-22 | £ 65000 / year
A Data and Application Engineer role in a hybrid London setting involves designing ETL pipelines, automating key processes, and building data-driven solutions with expertise in Azure Data Factory,... read more »
ETL/ELT, Data Engineering, ADF, Databricks, SQL, Data Modelling, Data Quality, Agile/Scrum