Jobs at Databricks

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 and grow an enterprise sales team responsible for quota attainment, new-logo acquisition, Databricks usage growth, forecasting, and customer outcomes. Build trusted customer and partner relationships, develop enterprise territories, promote value-based selling, and foster a high-performance culture. The role requires leading account executives in Big Data, cloud, analytics, and AI markets while supporting regional growth plans and partner ecosystems.

Sell Databricks enterprise cloud data platform to Financial Services customers. Manage full sales cycle with CIOs and IT/LOB execs, close new and expansion deals, track pipeline in Salesforce, exceed quota, and drive customer satisfaction and internal account plans.

Provide corporate legal support across M&A, venture and capital transactions, securities compliance and public-company readiness, governance, board materials, disclosure controls, antitrust counseling, international subsidiary management, ESG reporting, and cross-functional stakeholder advising to scale legal processes for a fast-growing technology company.

Lead strategic enterprise sales within CMEG accounts by building C-level relationships, driving value-based growth, expanding Databricks adoption, exceeding pipeline and revenue targets, managing forecasting in Salesforce, and positioning Databricks' Data + AI platform for new use cases and business units.

Customer-facing senior engineer who architects, builds, and productionizes data and AI solutions on the Databricks platform. Leads end-to-end projects spanning data engineering, distributed Spark systems, MLOps, and user-facing applications, embeds with stakeholders, delivers measurable outcomes, and contributes reusable assets and best practices.

Lead day-to-day operation and maturation of Databricksprivacy compliance program, develop AI-enabled controls, run privacy by design and risk assessments, manage data subject rights, contracts (DPAs, SCCs), regulatory engagement, incident response, policy development, cross-functional training, and continuous process improvement across the company.

Lead customer-facing projects to design, build, and productionize end-to-end data and AI solutions on Databricks. Own architecture, implement data pipelines, ML/AI integrations, applications, and reusable assets. Embed with customers, guide adoption, manage technical delivery, and collaborate cross-functionally to drive measurable outcomes.

Lead and operate the Product Legal program: own workstreams, build and maintain Jira automations, route and track legal requests, develop AI tooling and agents to automate legal tasks, maintain operational dashboards, and coordinate compliance rollouts while driving continuous process improvements across legal, engineering, and product teams.

Own customer-facing AI and data engagements from discovery through production launch. Define business value, MVPs, success criteria, and product requirements; prioritize engineering backlogs; lead technical discovery, architecture reviews, agile delivery, testing, production readiness, launch, adoption, and strategic handoff. Build C-suite relationships, translate business needs into technical requirements, resolve delivery risks, and identify future high-value opportunities.

Leads Databricks’ global customer enablement partnerships, owning strategy, operating models, commercialization, partner offerings, pricing, governance, quality standards, and revenue growth. The role coordinates Legal, Finance, Curriculum, Training Operations, Commercialization, and regional teams while scaling partner-led curriculum, certification, and delivery programs. It also develops regional capabilities, manages global partnership ecosystems, and champions AI-enabled expansion.

Drive enterprise sales of Databricks’ Data Intelligence Platform to Fortune 500 and telecommunications accounts. Build executive relationships, expand usage across business units, manage strategic opportunities, exceed pipeline and revenue targets, forecast in Salesforce, and lead value-based solution selling. The role requires expertise in big data, cloud, SaaS, AI, and consumption-based sales motions, along with the ability to translate technical capabilities into business value.

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.

Lead technical strategy for customer accounts, design scalable data engineering and real-time analytics architectures, and drive Databricks adoption. Advise senior customer stakeholders, lead architecture discussions, develop custom solutions for competitive opportunities, coordinate cross-functional teams, and influence product direction. The role requires deep expertise in Spark, Kafka, data warehousing, cloud platforms, Python, SQL, distributed systems, and production deployments. Travel may reach 30%.

Advise enterprise customers on designing, securing, administering, and deploying Databricks environments on Microsoft Azure. Architect scalable cloud infrastructure, networking, identity, disaster recovery, observability, and infrastructure-as-code solutions. Support pre-sales activities through proof-of-concept architectures and technical content, while sharing expertise through training, tutorials, hackathons, conferences, and open-source contributions.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.

Own the vision, strategy, and roadmap for Databricks’ AI-first learning platform. Build contextual guidance, adaptive learning paths, learner models, assessments, skills graphs, analytics, and personalization tools. Partner with engineering, UX, curriculum, education, and go-to-market teams to deliver scalable learning experiences for customers, partners, and employees. Define metrics, understand skills gaps, engage users, and improve platform adoption through embedded learning capabilities.

Lead technical strategy for customer accounts by designing scalable data, AI, streaming, and analytics architectures on Databricks. Advise senior technical stakeholders, drive platform adoption and consumption growth, conduct architecture discussions, build competitive solutions, coordinate cross-functional resources, and provide product feedback. The role requires strong Python and SQL coding, public-cloud deployment experience, distributed data systems expertise, and excellent technical communication.

Leads and scales a customer-facing AI Forward Deployed Engineering team, overseeing hiring, mentoring, strategic AI initiatives, enterprise engagements, and production AI delivery. Builds executive customer relationships, partners with Sales, Product, Engineering, and GTM, influences product strategy through customer insights, manages account and services outcomes, and represents Databricks as an AI thought leader.

Guide enterprise customers in designing, securing, administering, and deploying Databricks environments on AWS. Architect scalable infrastructure, networking, identity, and security solutions; support pre-sales engagements through proofs of concept and technical content; and provide technical leadership, training, tutorials, and community contributions. The role requires expertise in AWS, distributed data architectures, infrastructure automation, programming, SQL, and customer-facing technical consulting, with travel up to 30%.