Cloud Hyperscalers & Modern Data Platforms
Comparative telemetry tracking adoption, market share, and enterprise hiring across the Big 3 Hyperscalers (AWS, Azure, GCP) and leading modern data platforms (Databricks, Snowflake, BigQuery, Redshift, Microsoft Fabric).
Total Cloud Openings
1,035
Active job postings explicitly requiring cloud infrastructure
Multi-Cloud Coexistence
51.9%
Positions requiring or accepting 2 or more cloud platforms
Hyperscaler Leader
AWS vs Azure vs GCP
AWS (12.4%) closely followed by Azure (11.0%) and GCP (10.8%)
Lakehouse vs. DWH
535 vs 310
Databricks (535 jobs) vs. Snowflake (310 jobs)
The Cloud Wars: Market Penetration of Cloud & Data Platforms
Active job postings explicitly requiring the platform across 500+ enterprises
| Metric / Technology | Active Postings |
|---|---|
| AWS | 758 |
| Microsoft Azure | 666 |
| Google Cloud Platform | 638 |
| Databricks | 541 |
| Snowflake | 315 |
| BigQuery | 112 |
| Amazon Redshift | 55 |
| Microsoft Fabric | 33 |
Multi-Cloud Interoperability & Overlap
Enterprise demand for multi-cloud competencies across the Big 3
Over 51% of enterprise cloud postings demand or accept multi-cloud skills, showing that single-vendor lock-in is increasingly rejected in enterprise data architectures.
Google Cloud Platform (GCP) Deep-Dive
BigQuery, Vertex AI, Dataform SQLX, Dataflow streaming, and Looker semantic layer telemetry.
Demand for Specific Google Cloud Services
Active job postings in the current snapshot
| Metric / Technology | Positions |
|---|---|
| Google Cloud Platform | 638 |
| BigQuery | 112 |
| Vertex AI | 73 |
| Looker | 63 |
| Google Cloud Dataflow | 26 |
| Dataform | 2 |
Top Roles Operating on the GCP Ecosystem
Distribution of canonical roles requiring GCP / BigQuery / Vertex AI
| Metric / Technology | GCP Positions |
|---|---|
| AI Developer | 209 |
| Machine Learning Engineer | 208 |
| Data Engineer | 109 |
| Data Scientist | 53 |
| Data Architect | 46 |
| Data Analyst | 29 |
| Engineering Manager (AI/Data) | 12 |
| AI / Data Product Manager | 12 |
Detailed Telemetry of Tracked GCP Services
Google Cloud Platform
638 postings (10.59% of market)
Most frequently paired with:
BigQuery
112 postings (1.86% of market)
Most frequently paired with:
Vertex AI
73 postings (1.21% of market)
Most frequently paired with:
Looker
63 postings (1.05% of market)
Most frequently paired with:
Google Cloud Dataflow
26 postings (0.43% of market)
Most frequently paired with:
Dataform
2 postings (0.03% of market)
Most frequently paired with:
Architectural Notes & Production Insights
BigQuery & BigLake
The foundational analytical engine on GCP. Dominates enterprise architectures through decoupled compute/storage, native Apache Iceberg support via BigLake, and in-warehouse ML/LLM execution (BigQuery ML).
Vertex AI & Agent Builder
Unified platform for deploying Gemini and open-weight models, managing low-latency Vector Search, running automated Rapid Evaluations, and orchestrating production AI agents.
Dataform (in BigQuery)
Native ELT transformation orchestrator inside BigQuery built on SQLX. Enables Git-versioned data models, automated data quality assertions, and dependency graphs without external infrastructure.
Looker & Semantic Layer
Mission-critical semantic layer (LookML) defining unified business metrics across the enterprise. In the GenAI era, it serves as a deterministic grounding layer that prevents metric hallucinations.
Top Corporations Hiring for This Stack (GCP)
BigQuery, Vertex AI, Dataform SQLX, Dataflow streaming, and Looker semantic layer telemetry.
Amazon Web Services (AWS)
AWS remains the volume leader in total job postings, driven by ubiquity in core compute (EC2/EKS), object storage (S3 as the default data lake substrate), and specialized analytical engines (Amazon Redshift, EMR, Athena, Glue). Modern enterprise data teams frequently run Databricks or Snowflake on top of AWS storage.
Top In-Demand Roles:
Top Corporations Hiring for This Stack:
Microsoft Azure & Fabric
Microsoft Azure maintains strong enterprise momentum through deep integration with the Microsoft 365 ecosystem, Power BI, and Azure OpenAI Service. The arrival of Microsoft Fabric represents a strategic shift toward an all-in-one SaaS lakehouse engine competing directly with Snowflake and Databricks.
Top In-Demand Roles:
Top Corporations Hiring for This Stack:
Databricks vs. Snowflake: Lakehouse vs. Cloud DWH
The defining architectural battle in modern data platforms is between Databricks (pioneering the Lakehouse with Apache Spark, Delta Lake, and Unity Catalog) and Snowflake (expanding from cloud data warehousing into Iceberg tables, Snowpark, and Cortex AI). Our telemetry shows Databricks leading with 535 active postings vs. Snowflake with 310 postings.
Top Corporations Hiring for This Stack:
Top Corporations Hiring for This Stack:
Cloud Stack Co-occurrence Matrix
v_skill_cooccurrenceTelemetry showing which technology pairs most frequently appear together in the same job posting requirements.
Author Deep-Dives from akucera.eu & Substack
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