Jobs at Databricks

Sell Databricks’ cloud data platform to financial services organizations, focusing on net-new logo acquisition and account expansion. Build relationships with CIOs, IT and line-of-business executives, and program managers; manage short and complex sales cycles; exceed pipeline, activity, and revenue targets; track forecasting and customer details in Salesforce; communicate complex cloud technologies; and close solution-based enterprise deals.

Provides U.S. and global employment-law advice on compensation, benefits, pay equity, recruiting, mobility, immigration, employee privacy, HR AI, and M&A. Drafts employment documents, supports disputes, leads cross-border projects, advises on workforce technology and AI governance, monitors legal developments, and develops scalable legal processes. Partners with People, recruiting, privacy, tax, security, corporate development, and regional legal teams in a fast-moving technology company.

Build and improve ML and LLM systems for CustomerLake personalization use cases, including recommendations, targeting, churn, and lifetime-value modeling. Develop production evaluation and monitoring frameworks tied to business outcomes, inspect model behavior, and advance novel methods. Partner with product, engineering, and design to create scalable solutions, establish ML/AI best practices, and lead ambiguous 0-to-1 initiatives from concept through launch and adoption.

Provide end-to-end product legal counsel to engineering, product, marketing, commercialization, and communications teams. Advise on data privacy, AI, cybersecurity, technology transactions, product risks, and global regulations. Draft and negotiate product and security-related agreements, including DPAs and BAAs; assess vendor data flows; support incident response; and improve legal processes. The role requires strong business judgment, technical understanding, communication skills, and at least eight years of relevant legal experience with state bar membership.

Enterprise Account Executive responsible for selling Databricks’ cloud data platform to enterprise customers. Duties include developing territory plans, engaging CIOs and business leaders, closing new and existing accounts, managing complex sales cycles, exceeding pipeline and revenue targets, forecasting in Salesforce, and communicating the value of cloud, SaaS, and big data solutions. Requires 7+ years of enterprise sales experience and familiarity with Spark and big data.

Build and execute Databricks’ venture capital and private equity ecosystem strategy. Develop investor relationships, create founder and portfolio-company programs, generate qualified introductions, and connect companies with sales and technical teams. Lead workshops, briefings, events, portfolio reviews, and executive communications while measuring program conversion and value. Collaborate with startups, sales, field engineering, marketing, and partners to deliver data and AI outcomes, strengthen investor engagement, and support new-account acquisition and expansion.

The Startup Account Executive will prospect for and close new startup accounts while expanding existing customer relationships. Responsibilities include building territory plans, prioritizing accounts, communicating the Databricks Lakehouse vision, managing transactional and strategic sales cycles, achieving pipeline and revenue targets, and maintaining accurate Salesforce and Clari records. The role requires at least one year of closing experience, preferably in big data, cloud, or SaaS sales, along with a demonstrated history of exceeding quotas.

Lead technical strategy for financial services customers by designing scalable data, AI, streaming, and analytics architectures. Own customer engagements from discovery through production deployment, advise senior technical stakeholders, drive Databricks adoption, lead competitive technical wins, coordinate cross-functional resources, and provide product feedback. The role requires strong Python and SQL coding, distributed data systems expertise, public cloud deployment experience, and the ability to translate complex architectures into business value.

Enterprise Geo Hunter Account Executive responsible for selling Databricks’ cloud data platform to financial services organizations. The role focuses on hunting net-new logos, expanding customer vision, managing complex and transactional sales cycles, exceeding quota, forecasting in Salesforce, and building executive relationships. Candidates need field sales experience in big data, cloud, or SaaS, a record of exceeding quotas, success closing new business, strong cloud technology communication skills, and preferably financial services and Apache Spark expertise.

Provides advanced, customer-facing technical support for strategic Databricks customers. Troubleshoots Spark, SQL, Delta, streaming, ML, and AI performance issues; performs root-cause analysis; develops proofs of concept, monitoring solutions, playbooks, and knowledge resources; trains customer teams; and collaborates with Field Engineering, R&D, Sales, Product, and NOC teams. Serves as a trusted technical advisor and advocates for customers. Requires approximately 20% travel.

Prospects and closes net-new enterprise accounts for Databricks’ cloud data platform. Develops account strategies, engages buying centers, identifies use cases, communicates technical and business value, orchestrates internal teams, negotiates deals, and exceeds sales quotas. The role requires SaaS, cloud, or big data sales experience, executive relationships, and the ability to sell complex technology to digital-native customers.

Leads strategic partnerships with cloud hyperscalers and neoclouds, negotiating bespoke commercial agreements and developing long-term growth opportunities. Collaborates with product, engineering, finance, sales, and marketing teams; builds executive relationships; creates data-driven business cases; influences product decisions; and establishes KPIs to measure partnership success. Requires extensive business development experience, cloud consumption-model expertise, strong analytical and presentation skills, and the ability to independently lead complex deals.

Own global accounts receivable month-end close, including subledger-to-GL reconciliations, AFDA/CECL modeling, accruals, reporting, and balance sheet integrity. Apply U.S. GAAP, maintain audit-ready workpapers and SOX controls, and partner cross-functionally across Order-to-Cash and Finance teams. Lead AI and automation adoption using Databricks and advanced analytics, while supporting SAP and other finance systems implementations. Drive scalable process improvements in a high-growth technology environment.

Own customer-facing AI and data engagements from discovery through production launch. Define business value, pilot MVPs, success criteria, and product requirements; prioritize engineering backlogs; lead technical discovery and architecture discussions; manage agile delivery, testing, security, performance, adoption, and stakeholder alignment. Partner with executives, sales, and engineers to deliver production-ready solutions and identify follow-on opportunities.

Lead customer-facing technical discovery, solution architecture, proofs of concept, platform demonstrations, and architecture reviews for data engineering, analytics, and machine learning workloads. Develop account-level technical strategies with Account Executives, explain competitive differentiation, and build reusable notebooks, accelerators, and reference architectures. The role requires hands-on coding, cloud data platform expertise, distributed systems knowledge, strong presentation skills, and technical customer leadership.

Senior legal counsel supporting international channel and partner programs for a high-growth technology company. Responsibilities include drafting and negotiating partner agreements, developing scalable channel models, assessing compliance risks across jurisdictions, advising on privacy, security, AI, and intellectual property issues, creating training, and collaborating with commercial, operations, compliance, and business teams.

Build and productionize customer-facing data and AI solutions on the Databricks Platform. Own architecture, design, implementation, deployment, and integration of data pipelines, distributed systems, ML/AI models, and applications. Guide enterprise customers, manage technical delivery, train stakeholders, resolve implementation issues, and create reusable frameworks. Collaborate with engineering, product, project management, support, and customer teams while traveling to customers approximately 20% of the time.

Lead the design and development of sales data models, CRM-integrated AI agents, and permissioned write paths for revenue teams. Build scalable GenAI interfaces for complex workflows with transparency and human approval. Partner with product, design, and engineering teams to define initial use cases, launch MVPs, and drive adoption. Provide technical and people leadership in a 0-to-1 product environment.

Leads scalable advertising data ingestion, normalization, aggregation, identity resolution, and agentic workflow development. Establishes correctness and evaluation standards for noisy measurement data, while partnering with product, design, and engineering teams to deliver scalable solutions. Requires deep advertising API and ad-tech measurement expertise, production LLM experience, and technical and people leadership in complex enterprise environments.

Leads customer technical strategy, architecture discussions, Databricks adoption, and production deployments. Designs scalable solutions across data engineering, machine learning, AI, real-time analytics, distributed data systems, streaming, lakehouse architectures, and cloud platforms. Advises senior technical stakeholders, drives competitive technical wins, coordinates cross-functional resources, develops technical specialization, and influences product direction through customer feedback.