Databricks

big data, analytics, spark
Databricks logo
Open jobs

3264

Companies looking for

2929

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.

Used together with Databricks

Additional Resources

Compare to other data warehouses
Jobs (this month)

3264

Companies with Jobs

2929

Jobs in using Databricks for but please no

data scientist

Data Scientist II – QuantumBlack, AI by McKinsey @ quantumblack

GB | 2025-12-28
London-based Data Scientist II at QuantumBlack promises a fast-track in a high-performance, client-facing lab where ML meets real business impact. The role blends model work with production... read more »
Analytics, R, AI/ML, PhD, Computer Science, SQL, Python, Data Science, Big Data, PySpark, Hive, Hadoop, SPSS, SAS, Airflow, Databricks, Docker, Kubernetes, Cloud Computing, AWS, GCP, GenAI, Management
data scientist

Data Scientist I - QuantumBlack, AI by McKinsey @ quantumblack

GB | 2025-12-26
McKinsey’s Data Scientist I in London promises a client-facing, high-velocity path that blends analytics, code, and real business impact. You’ll translate business needs into models, collaborate... read more »
Analytics, R, AI/ML, PhD, Computer Science, Python, SPSS, SAS, PySpark, SQL, Airflow, Databricks, Docker, Kubernetes, Cloud Computing, AWS, GCP, GenAI, Management
promoted

O'Reilly: Building AI Agents with Model Context Protocol (MCP)

Design and implement composable agent architectures using MCP. Understand the MCP architecture and how it enables AI applications to access external context. Build MCP servers that expose tools, resources, and prompts to LLMs.

Get Started
data scientist

Senior Machine Learning Engineer - ML Infrastructure @ asos-com

GB | 2025-12-25
ASOS seeks a Senior Machine Learning Engineer to develop reusable templates, deployment patterns, and MLOps tooling aimed at standardizing ML workflows across the organization. The role emphasizes... read more »
AI/ML, MLOps, Marketing, CI/CD, Management, Data Engineering, Python, PyTorch, TensorFlow, Docker, Kubernetes, Cloud Computing, Azure, Spark, Databricks