Databricks users list

Email list of companies using Databricks

Q: How many companies use Databricks?

Data InfoMetrix tracks 39,683 companies using Databricks, with 238,982 verified contacts at those accounts as of October 2026. The largest groups are Pharmaceuticals & Precision Medicine, Tier-1 Financial Services & FinTech and Autonomous Mobility & Automotive. Counts are estimates from our database and market research, so ask us for a live count for your exact criteria.

Q: Who buys and manages Databricks inside a company?

Databricks is usually owned by Data Science, Machine Learning & AI Engineering Leadership. Decision-makers include Chief Data Officer (CDO), VP of Artificial Intelligence and Head of Data Science; Principal ML Engineer and Lead Data Architect shape the choice, and Machine Learning Engineers and Data Scientists use it day to day. Our Databricks list can include any of these roles.

Q: Which Databricks products or editions can I target?

You can target accounts by the Databricks products they run, including Databricks Lakehouse Platform (Delta Lake Engine), Databricks Unity Catalog (Unified Governance & Lineage), Databricks Mosaic AI & MLflow Model Registry, Databricks SQL Warehouses & Serverless Compute and Delta Live Tables (DLT) & Streaming Pipelines. Tell us which edition or module matters and we filter the list to those accounts.

Q: What does Databricks integrate with?

Databricks is most often connected to Snowflake, dbt Labs, Apache Spark, Power BI and Tableau, so users of those tools overlap heavily with Databricks accounts. We can filter any list by this kind of stack overlap.

Q: What are the main alternatives to Databricks?

The main alternatives to Databricks are Snowflake Snowpark, Google BigQuery AI, Amazon SageMaker and Microsoft Fabric. We also keep verified user lists for Snowflake Snowpark, which is useful for competitive displacement campaigns.

Q: What challenges do Databricks customers face?

Common challenges for Databricks accounts include Cluster Sizing Inefficiency & Unchecked DBU Compute Burn, Unity Catalog Migration & Multi-Workspace Permission Sprawl and Production MLOps Bottlenecks & Feature Store Latency. Data science teams spinning up large interactive GPU/CPU Spark clusters for exploratory analysis frequently leave instances idle, generating massive DBU cost overruns that alarm finance leads. These are good angles for outreach to Databricks users.

Q: Can Data InfoMetrix deliver a free sample Databricks contact list before ordering?

Yes. Data InfoMetrix delivers a complimentary 10-record sample tailored to your target Databricks criteria—including target job titles, company size, and region—delivered within one business day with no obligation.

Q: How does Data InfoMetrix guarantee email deliverability for Databricks contacts?

Data InfoMetrix provides a 99% email deliverability guarantee on all Databricks datasets. Every contact record undergoes real-time email verification within a 30 to 45-day refresh cycle, backed by a 1:1 hard bounce replacement policy for 30 days after delivery.

Access verified Chief Data Officers, Heads of AI/ML, and Principal Data Architects operating Databricks. You can filter by DBU compute consumption, Unity Catalog governance, MLflow model registry status, and verified direct dials with 99% deliverability.

39,683+Companies

238,982+Contacts

Updated Oct 7, 2026GDPR · CCPA99% accuracy

See sample data

Free Databricks count + 10 sample records

39,683+ companies · 238,982+ contacts available

✓Exact count for your titles, regions and company size
✓10 verified sample records to check quality
✓Price quote within 1 business day

Trusted by B2B and enterprise revenue teams

How many companies use Databricks?

Data InfoMetrix tracks 39,683+ companies running Databricks as of October 2026, with 238,982+ verified contacts at those accounts. The largest groups are Pharmaceuticals & Precision Medicine, Tier-1 Financial Services & FinTech and Autonomous Mobility & Automotive. Buying decisions usually sit with the Chief Data Officer (CDO), VP of Artificial Intelligence and Head of Data Science. Counts are estimates built from technology footprint scans, job-post signals and partner directories, checked by our research team. How we count

Tracked accounts39,683+

Organizations detected running Databricks.

Verified contacts238,982+

Direct emails and phone dials for decision-makers.

Primary personasVP of Data Science & AI, Head of Machine Learning Engineering, Chief Data Architect

Full buying committee mapped.

Deliverability SLA99%

SMTP-verified, with 1:1 replacement of any email that hard bounces within 30 days.

Data specification · Updated Q4 2026

Technology category	Data Analytics & Modern Data Stack
Tracked organizations	39,683+ verified accounts worldwide
Decision-maker contacts	238,982+ records with emails, mobile and direct dials
Key roles	VP of Data Science & AI, Head of Machine Learning Engineering, Chief Data Architect, platform administrators, IT directors, procurement
Geography	180+ countries · country-by-country counts on request
Verification	DNS and script telemetry, 5-stage SMTP handshake, manual research
Refresh cadence	Continuous, 30–45 day maximum record age at delivery
Compliance	GDPR, CAN-SPAM, CCPA and CASL
Delivery	24–48 hours as CSV, XLSX or CRM API

Editorial & verification

Researched by the Data InfoMetrix research team. Counts updated October 2026.

How we count and verify data

Market guide

Selling to Databricks customers

Databricks is a data and AI platform built on the lakehouse model. Its customers combine data engineering, analytics and machine learning, and they buy tools for governance, observability and AI.

Written by the Data InfoMetrix research team · Updated October 2026

Who runs Databricks

Databricks is used by enterprises in financial services, retail, manufacturing, healthcare, media and technology, often by teams that run large Spark workloads, machine learning and now generative AI. Unity Catalog provides governance, and Mosaic AI supports model building and serving.

Who to contact

Chief Data Officers, VPs of Data and Heads of AI or ML own strategy. Data platform leads, data engineering managers and ML engineering leads choose tools, and security and governance teams own access and compliance.

When Databricks accounts are ready to buy

Migrating from Hadoop or legacy warehouses, adopting Unity Catalog, launching generative AI applications and reviewing consumption costs are the main triggers.

How to segment and approach

Segment by cloud, by workload (engineering, analytics, ML) and by the tools around it: Snowflake (many companies run both), dbt, Kafka and MLflow. Accounts with both Databricks and Snowflake have complex data estates.

Lead with concrete gains in pipeline reliability, governance and cost, and show how you work with Delta Lake and Unity Catalog.

Size your Databricks audience

Pick a region, company size and buying role to estimate how many accounts and contacts you can reach.

Region

Company size

Buying role

Estimated segment✓ 99% SLA

39,683+Target accounts

238,982+Direct contacts

Decision-makers35%

Influencers45%

End users20%

Estimates from our current Databricks dataset. Exact counts come with your quote.

Reach the whole buying committee

A Databricks account is not one contact. We map the people who evaluate, buy, run and use it across Data Science, Machine Learning & AI Engineering Leadership.

Decision-makersC-suite & sponsors

Chief Data Officer (CDO)VP of Artificial IntelligenceHead of Data ScienceVP of Software Engineering

Influencers & adminsEvaluate & configure

Principal ML EngineerLead Data ArchitectMLOps SpecialistAnalytics Infra Lead

End usersRun it every day

Machine Learning EngineersData ScientistsBig Data DevelopersData Analysts

These are examples. We build records for any department, seniority or custom title.

See exactly what you get

Every record carries 60+ fields, from verified email, direct dial and LinkedIn to full postal address, Databricks edition, coexisting stack and intent.

Contact	Buying role	Work email	Direct dial	Company phone	Fax	LinkedIn profile	Company	LinkedIn company page	Industry	Address 1	Address 2	City	State	ZIP code	Country	Databricks footprint	Intent	Status
SPDr. Sanjay PatelChief Data Officer (CDO)	Decision Maker	s.pa**@apexfina******.com	+1 (212) 55*-**	+1 (212) 55*-**	+1 (212) 55*-**	linkedin.com/in/s*ay-pa******	Apex Financial Intelligence Group Inc.	linkedin.com/company/apex-fin-analytics	Financial Services & Investment Research	200 Park Ave 42nd	Fl	New York	NY	10166	United States	Databricks Data Intelligence Platform (Lakehouse Architecture + Delta Lake)	High	✓ Verified 2026
TSTheresa SterlingVP of Data Engineering & Infrastructure	Decision Maker	t.ste**@novac**.io	+1 (415) 55*-**	+1 (415) 55*-**	+1 (415) 55*-**	linkedin.com/in/t*esa-st*******	Nova Cloud Communications Inc.	linkedin.com/company/nova-cloud-tech	Cloud Infrastructure & High-Volume Telemetry	350 Mission St	Ste 1800	San Francisco	CA	94105	United States	Databricks Unity Catalog Centralized Governance & Lineage	High	✓ Verified 2026
MBMaximilian BauerDirector of Business Intelligence & Analytics	Influencer	m.ba**@bavaria****.de	+49 (89) 55*-**	+49 (89) 55*-**	+49 (89) 55*-**	linkedin.com/in/m*ilian-********	Bavaria Digital Retail Group AG	linkedin.com/company/bavaria-retail-ag	Omnichannel Retail & E-Commerce	Maximilianstraße 35	—	Munich	Bavaria	80539	Germany	Databricks SQL Serverless Warehouses & Photon Engine	Medium	✓ Verified 2026
COClara OswaldLead Analytics Engineer & Data Architect	Practitioner	c.os**@beaconhe*****.uk	+44 (20) 79*-**	+44 (20) 79*-**	+44 (20) 79*-**	linkedin.com/in/c*a-os******	Beacon Clinical Healthcare Analytics Ltd	linkedin.com/company/beacon-clinical-data	Health Analytics & Clinical Research	25 Finsbury Circus	—	London	Greater London	EC2M 7EE	United Kingdom	Databricks Mosaic AI Model Training & Fine-Tuning	High	✓ Verified 2026
RLRobert LangdonHead of Enterprise Data Governance & Compliance	Decision Maker	r.lan**@prudenti*****.com	+1 (312) 55*-**	+1 (312) 55*-**	+1 (312) 55*-**	linkedin.com/in/r*rt-la*******	Prudential Trust & Bancorp Inc.	linkedin.com/company/prudential-trust-bancorp	Commercial Banking & Wealth Management	111 W Monroe St	Ste 2200	Chicago	IL	60603	United States	Databricks Delta Live Tables (DLT) Streaming Pipelines	Medium	✓ Verified 2026
NSNadia SolokovaDirector of Machine Learning & Applied AI Data	Influencer	n.sol**@quant***.com	+1 (617) 55*-**	+1 (617) 55*-**	+1 (617) 55*-**	linkedin.com/in/n*a-sol******	Quantum Insurance Risk Modeling LLC	linkedin.com/company/quantum-insurance-data	Property & Casualty Insurance Actuarial Data	100 Cambridge St 14th	Fl	Boston	MA	02114	United States	Databricks Feature Store for Real-Time ML Inference	High	✓ Verified 2026
AMAlain MercierVP of Global Enterprise Architecture	Decision Maker	a.mer**@telecom****.fr	+33 (1) 44*-**	+33 (1) 44*-**	+33 (1) 44*-**	linkedin.com/in/a*n-mer******	Telecom France Networks SA	linkedin.com/company/telecom-france-networks	Telecommunications & Cellular Data Networks	78 Rue de Vaugirard	—	Paris	Île-de-France	75006	France	Databricks Workflows Orchestration & Job Monitoring	High	✓ Verified 2026
HOHiroshi OgawaSenior Data Platform Solutions Architect	Practitioner	h.og**@tokyodig*****.jp	+81 (3) 55*-**	+81 (3) 55*-**	+81 (3) 55*-**	linkedin.com/in/h*shi-o*******	Tokyo Digital Media Systems KK	linkedin.com/company/tokyo-digital-media	Digital Entertainment & Media Streaming Data	GranTokyo South Tower	32F	Tokyo	Tokyo	100-6632	Japan	Databricks Clean Rooms for Cross-Company Data Collaboration	Medium	✓ Verified 2026

Illustrative rows showing 20 of 60+ fields. Full records are unmasked.

We deliver 60+ data fields per record, including intent data. The sample shows a selection only. Tell us which fields you need, including any that aren't listed here, and we'll add them to your list.

Also available:Seniority & departmentJob functionTenure in roleEmployee countAnnual revenueSIC & NAICS codesParent companyWebsite & domainProduct editionContract & renewal timingIntent topics & scoreEmail verification date

How we prove an account runs Databricks

No scraped résumés or stale directories. Three layers confirm a live installation before a contact reaches your list. Read our verification protocol

Pillar 1 · Telemetry

Live DNS & script signals

We inspect response headers, DNS MX and CNAME records and live JavaScript bundles to confirm a running Databricks instance.

DNS · CNAME · MX recordsHTTP headers · JS bundles✓ Verified against live infrastructure

Pillar 2 · Operational intent

90-day hiring signals

We track job requisitions that ask for Databricks skills, which shows ongoing budget and headcount.

Now hiringDatabricks Administrator

Now hiringDatabricks Architect

Now hiringDatabricks Engineer

Pillar 3 · Human & mailbox QA

Pre-delivery SMTP handshake

Each email is tested against the destination mail server, and titles are checked against current company rosters.

SMTP check ✓LinkedIn match ✓Title verified ✓

✓ Deliverable inbox and current role

Deliverability SLA

<3%

Maximum bounce rate, or we replace the contacts. Your sender reputation stays clean.

1:1 hard bounce replacement

Every email that hard-bounces within 30 days of delivery is replaced free, record for record.

24-hour pre-delivery ping

Live SMTP and MX checks right before we send your file.

Instant CRM import

Clean CSV or XLSX, ready for one-click import.

Ready for your outbound stack

Imports straight into the tools you use.

What are you trying to do?

Each campaign needs a different data strategy. Pick your goal to see how we build the audience.

Find companies on rival platforms and reach the people evaluating a move to, or away from, Databricks.

Conquesting playbook

Pitch integrations, add-ons and complementary tools to companies already running Databricks.

Ecosystem playbook

Build account lists around Databricks deployment scale and engage the full committee across departments.

ABM playbook

Conquesting audienceSample

Snowflake Snowpark

Google BigQuery AI

Amazon SageMaker

→

Databricks

Know the stack around every account

Databricks rarely runs alone. Every record is tagged with the tools detected alongside it, so you can segment by complementary stacks.

dbt

Open the coexistence matrix

What Databricks customers look like

Anonymised profiles of companies in our Databricks dataset of 39,683+ accounts. Named accounts are shared in your free sample, never on a public page.

Databricks account profiles · anonymised

Company size	Industry	Country	Employees	Revenue
Mid-market	Autonomous Mobility & Automotive	Australia	500–999	$100M–$250M
Mid-market	Energy, Oil & Gas Modeling	United States	200–999	$50M–$250M
Enterprise	High-Scale SaaS & Digital Media	United States	5,000+	$1B+
Upper mid-market	Pharmaceuticals & Precision Medicine	United Kingdom	1,000–4,999	$250M–$1B
SMB	Tier-1 Financial Services & FinTech	United States	50–199	$10M–$50M
Enterprise	Autonomous Mobility & Automotive	Canada	10,000+	$5B+
Mid-market	Energy, Oil & Gas Modeling	Germany	500–999	$100M–$250M
Mid-market	High-Scale SaaS & Digital Media	United States	200–999	$50M–$250M

Markets we cover

United States

India

United Kingdom

Canada

Germany

Australia

Singapore

France

New Zealand

Netherlands

Plus 170 more countries. Ask for a country-by-country count of Databricks accounts and we'll include it with your free sample.

Build the list your way

Every list is assembled from source to your product tier, job function, geography and revenue band. Nothing is a fixed export.

Editions & modules

Filter by what they actually run.

+Databricks Lakehouse Platform (Delta Lake Engine)+Databricks Unity Catalog (Unified Governance & Lineage)+Databricks Mosaic AI & MLflow Model Registry+Databricks SQL Warehouses & Serverless Compute+Delta Live Tables (DLT) & Streaming Pipelines

Firmographics

Match revenue, size and industry.

+Industry+$1M–$10B+ revenue+Headcount+Ownership & funding+HQ & branches

Geography

Target any territory.

+US & Canada+US states+UK, DACH, Nordics+APAC & ANZ+Metro clusters

Need multi-attribute segments? Open the Audience Builder

What Databricks teams are struggling with

Know the friction before you reach out, and position your product where it matters.

Friction 1

Runaway Compute Credit Consumption & Warehouse Cost Spikes in Databricks

ImpactEnterprise data teams face unexpected quarterly invoice surges as data volume scales.

OpportunityData warehouse cost optimization, dbt model efficiency auditing, and FinOps for data engineering.

Friction 2

Data Pipeline Failures & Stale Executive Dashboards

ImpactExecutive leadership makes key strategic decisions on broken or outdated metrics due to ETL/ELT pipeline lags.

OpportunityData observability platforms, automated data quality testing, and pipeline alert automation.

Friction 3

Siloed Data Lakes & Strict PII Data Governance Enforcement

ImpactData science & analytics teams wait weeks for secure access to anonymized production datasets.

OpportunityEnterprise data cataloging, automated PII masking, and data access governance tools.

Intent triggers we track

✓Migrating legacy data warehouses to Databricks cloud infrastructure

✓Implementing real-time streaming analytics and dbt transformation pipelines

✓Deploying machine learning models and generative AI workloads

✓Establishing centralized data governance and automated PII masking

“When you talk to companies who already use Snowflake and AWS about a native integration, the conversion rate skyrockets. Data InfoMetrix gave us the exact user list we needed.”

Director of Growth, a data integration companyName withheld at the client's request

Read the 6.8% Response case study

Databricks list questions, answered

How many companies use Databricks?

Data InfoMetrix tracks 39,683 companies using Databricks, with 238,982 verified contacts at those accounts as of October 2026. The largest groups are Pharmaceuticals & Precision Medicine, Tier-1 Financial Services & FinTech and Autonomous Mobility & Automotive. Counts are estimates from our database and market research, so ask us for a live count for your exact criteria.

Who buys and manages Databricks inside a company?

Databricks is usually owned by Data Science, Machine Learning & AI Engineering Leadership. Decision-makers include Chief Data Officer (CDO), VP of Artificial Intelligence and Head of Data Science; Principal ML Engineer and Lead Data Architect shape the choice, and Machine Learning Engineers and Data Scientists use it day to day. Our Databricks list can include any of these roles.

Which Databricks products or editions can I target?

You can target accounts by the Databricks products they run, including Databricks Lakehouse Platform (Delta Lake Engine), Databricks Unity Catalog (Unified Governance & Lineage), Databricks Mosaic AI & MLflow Model Registry, Databricks SQL Warehouses & Serverless Compute and Delta Live Tables (DLT) & Streaming Pipelines. Tell us which edition or module matters and we filter the list to those accounts.

What does Databricks integrate with?

Databricks is most often connected to Snowflake, dbt Labs, Apache Spark, Power BI and Tableau, so users of those tools overlap heavily with Databricks accounts. We can filter any list by this kind of stack overlap.

What are the main alternatives to Databricks?

The main alternatives to Databricks are Snowflake Snowpark, Google BigQuery AI, Amazon SageMaker and Microsoft Fabric. We also keep verified user lists for Snowflake Snowpark, which is useful for competitive displacement campaigns.

What challenges do Databricks customers face?

Common challenges for Databricks accounts include Cluster Sizing Inefficiency & Unchecked DBU Compute Burn, Unity Catalog Migration & Multi-Workspace Permission Sprawl and Production MLOps Bottlenecks & Feature Store Latency. Data science teams spinning up large interactive GPU/CPU Spark clusters for exploratory analysis frequently leave instances idle, generating massive DBU cost overruns that alarm finance leads. These are good angles for outreach to Databricks users.

Can Data InfoMetrix deliver a free sample Databricks contact list before ordering?

Yes. Data InfoMetrix delivers a complimentary 10-record sample tailored to your target Databricks criteria—including target job titles, company size, and region—delivered within one business day with no obligation.

How does Data InfoMetrix guarantee email deliverability for Databricks contacts?

Data InfoMetrix provides a 99% email deliverability guarantee on all Databricks datasets. Every contact record undergoes real-time email verification within a 30 to 45-day refresh cycle, backed by a 1:1 hard bounce replacement policy for 30 days after delivery.

Sourcing and compliance. Business contacts come from public company sources, professional directories and opt-in publishing partners, then go through SMTP verification and human review. Lists are for B2B outreach: include an unsubscribe link and honour opt-outs (CAN-SPAM), and have a lawful basis such as legitimate interest when you email people in the EU or UK (GDPR). Read how we source and verify data