Full-Time

Field Chief Technology Officer

Databricks

Databricks

10,001+ employees

Data lakehouse platform for analytics

Compensation Overview

$249.8k - $343.4k/yr

+ Bonus + Equity

United States

In Person

Category
Consulting (2)
,
Required Skills
Microsoft Azure
Data Science
Machine Learning
Data Engineering
AWS
Data Governance
Databricks
Google Cloud Platform
Requirements
  • 15+ years of experience spanning enterprise technology and consulting, including leading or advising on multi-year data platform and analytics transformations in large, complex organizations
  • Significant time spent inside a large enterprise software or cloud company (e.g., Microsoft or similar) in roles that required navigating matrixed organizations and driving change at scale, combined with direct industry exposure rather than a career spent solely in horizontal software
  • Experience in or with regulated industries (financial services, healthcare, public sector, regulated manufacturing, utilities), with familiarity with regulatory and compliance considerations affecting data and AI platforms
  • Background that blends: Hands-on technology and architecture work on data platforms and analytics; Organizational and operating model change (ways of working, skills, governance); Executive consulting or advisory, ideally seeing transformations through from strategy to multi-year execution, not only strategy decks
  • Proven ability to operate as a highly credible peer to C-level executives, driving business-outcome-focused conversations while also diving deep into technical details when needed
  • Strong, proactive networker who is naturally curious about which associations, councils, and forums matter for a given customer set, and who uses those networks to create new executive entry points and opportunities
  • Demonstrated longevity and impact in prior roles, with evidence of building and sustaining long-term customer relationships and programs rather than frequent short stints
Responsibilities
  • Build and maintain trusted-advisor relationships with C-level executives (CIO, CDO, CTO, CISO, business COs) in large US-based and global accounts, especially in highly regulated industries (financial services, public sector, healthcare, manufacturing).
  • Proactively cultivate a strong social and professional network across customer executives, boards, key industry bodies, and partners, knowing which organizations and forums to engage to open doors with the right stakeholders.
  • Shape executive thinking on modern data and AI architectures, with emphasis on Lakehouse and data platform modernization as the primary lever for long-term Gen AI impact.
  • Lead C-level briefings, strategy sessions, and multi-day workshops that connect business outcomes, regulatory constraints, and operating model change to concrete Databricks-based roadmaps.
  • Serve as a deep technical counterpart in the field, maintaining L200–L300 proficiency across Databricks products and being able to credibly engage architects, data engineers, and data scientists on solution design and trade-offs.
  • Generalize patterns from the field into reusable reference architectures, industry blueprints, and best practices for regulated industries, and share them through blogs, webinars, whitepapers, and conference keynotes.
  • Orchestrate the broader ecosystem (cloud providers, GSIs, consultancies, ISVs) around customer objectives, ensuring Databricks is at the center of multi-year transformation programs rather than isolated projects.
  • Partner with Account Executives, Solutions Architects, Industry Leads, and Product Specialists to drive complex, multi-year sales cycles, securing platform decisions and expansions while influencing ACV and consumption growth.
  • Provide structured, prioritized feedback from strategic customers into Product, Engineering, and Field leadership to influence product roadmap, especially around data, governance, security, and regulated-industry requirements.
  • Mentor senior Field Engineering and industry-focused talent, contributing to a pipeline of principal- and CTO-level leaders and codifying ways of working for complex, regulated accounts

Databricks provides a unified data and AI platform built around a lakehouse architecture that blends data lakes and data warehouses. It helps organizations ingest, store, manage, and analyze data from various sources, then apply analytics and machine learning at scale. The platform offers automated ETL, secure data sharing, and high-performance analytics, with built-in support for AI workloads and model deployment. Unlike traditional single-purpose data stores, Databricks combines data engineering, data science, and business analytics in one system, aiming to streamline data workflows and make insights readily actionable. Its goal is to enable businesses to manage data more efficiently, accelerate insight generation, and deploy AI and analytics across diverse teams through a subscription-based platform and professional services.

Company Size

10,001+

Company Stage

Debt Financing

Total Funding

$27.1B

Headquarters

San Francisco, California

Founded

2013

Simplify Jobs

Simplify's Take

What believers are saying

  • Asia-Pacific revenue surges 85% YoY in Q4, expanding to 32,000 sq ft Singapore office in 2026.
  • Acquires Antimatter and SiftD.ai to launch Lakewatch, adopted by Adobe and Dropbox.
  • Partners with UiPath and DBOS to enhance AI agent reliability and workflow orchestration.

What critics are saying

  • Snowflake Cortex AI erodes differentiation with cheaper serverless LLMs, churns customers in 6-12 months.
  • Microsoft Fabric's 5x faster queries collapse Azure customers' SQL pricing in 3-9 months.
  • Anthropic terminates Claude partnership in Q1 2026, obsoletes Lakewatch security in 12-24 months.

What makes Databricks unique

  • Databricks unifies data engineering, science, and business on Apache Spark-powered lakehouse.
  • Lakewatch delivers AI agentic SIEM using Anthropic's Claude for petabyte-scale threat detection.
  • Unity Catalog enforces unified governance across data, models, and dashboards.

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Your Connections

People at Databricks who can refer or advise you

Benefits

Extended health care including dental and vision

Life/AD&D and disability coverage

Equity awards

Flexible Vacation

Gym reimbursement

Annual personal development fund

Work headphones reimbursement

Employee Assistance Program (EAP)

Business travel accident insurance

Paid Parental Leave

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
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PR Newswire
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Persistent Systems has launched a Merchant Risk Management and Fraud Detection solution powered by Databricks' Data Intelligence platform. The solution uses Agentic AI to perform real-time merchant vetting during onboarding and continuous monitoring of transactions, chargebacks and third-party signals to detect fraud and compliance risks. Built on Databricks' platform, the solution triggers configurable actions when risk signals are detected, including enhanced monitoring or transaction restrictions. Persistent expects the solution to deliver a 20–40% reduction in fraud losses, 30–60% improvement in detection accuracy and 50–70% reduction in manual review effort. The solution is available now as a Databricks accelerator for banks, acquirers and payment service providers globally. Persistent is a Databricks Global Systems Integrator partner with over 900 certified professionals.

TechCrunch
Apr 8th, 2026
Databricks CTO wins computing award, says 'AGI is here already

Databricks co-founder and CTO Matei Zaharia has been awarded the 2026 ACM Prize in Computing, recognising his contributions including Apache Spark, the open source big data project he created during his PhD at UC Berkeley in 2009. The award includes a $250,000 prize, which Zaharia is donating to charity. Under Zaharia's engineering leadership, Databricks has grown into a cloud storage and AI data foundation giant, raising over $20 billion at a $134 billion valuation and achieving $5.4 billion in revenue. Zaharia believes artificial general intelligence already exists but argues we should stop applying human standards to AI models. He advocates for AI agents that leverage their unique strengths in data processing rather than mimicking human assistants, citing security risks. His focus is on AI-powered research automation across fields like biology and engineering.

PR Newswire
Apr 7th, 2026
DBOS partners with Databricks to boost agentic AI reliability and observability

DBOS, Inc. has announced a technology partnership with Databricks to enhance the reliability and observability of agentic AI workflows. The collaboration integrates DBOS's open-source durable execution platform with Databricks and Lakebase, Databricks' serverless Postgres database designed for AI agents. The partnership addresses challenges in agentic AI, including long-running workflows and unpredictable model responses. DBOS stores workflow checkpoints in Lakebase in real time, enabling AI agent workflows to resume automatically after failures without data loss. Yutori, an AI company building autonomous web agents, is already using the combined platform to power its workflows. The integration is available immediately and requires no additional infrastructure or coding changes. DBOS is backed by joint MIT-Stanford research and serves AI startups and Fortune 100 companies.

SiliconANGLE Media
Apr 7th, 2026
London AI security startup Trent AI raises $13M to protect AI agents from cyber threats

Trent AI, a London-based AI security startup, has launched with $13 million in seed funding led by LocalGlobe and Cambridge Innovation Capital. Executives from Databricks and Stripe also participated. Founded by former Amazon Web Services engineers Eno Thereska, Neil Lawrence and Zhenwen Dai, Trent AI has developed a platform that uses AI agents to identify cybersecurity issues in AI agents and their generated code. The platform employs four groups of agents that find exploits, rank vulnerabilities by severity, generate remediation suggestions, and track security changes over time. The platform can simulate complex attack paths and provides tool-specific features for OpenClaw and Lovable. Trent AI claims its technology outperforms traditional cybersecurity products designed for conventional software. The company will use the funding to expand its customer base and engineering team.