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 technical strategy for large enterprise accounts as Databricks’ primary technical voice. Partner with account executives and technical teams to drive data and AI transformation, product adoption, proofs of concept, and executive engagement. Build technical champions, align solutions to customer strategies, lead virtual teams, mentor colleagues, and demonstrate expertise in big data, data science, cloud, value selling, and production programming.

Develop customer engagement strategies, advise customers on data analytics architecture and Databricks adoption, lead complex proofs of concept, workshops, and technical engagements, and influence executives throughout the technical sales lifecycle. Coach junior Solutions Architects, collaborate with account executives and cloud ecosystem partners, create customer-facing collateral, and provide customized solutions for complex data challenges. Travel may reach 30%.

Perform inbound and outbound prospecting to build pipeline, partner with sales to develop territory strategy, identify Databricks use cases to grow consumption, and deliver a strong customer experience through solution-focused outreach and follow-up.

Build and productionize customer-facing data and AI solutions on the Databricks platform. Own architecture and design decisions, develop end-to-end data pipelines and applications, integrate ML/AI models, and guide deployment. Partner with customers, engineering, product, project managers, and support teams to deliver measurable outcomes. Train customers, resolve implementation issues, contribute reusable frameworks, and influence the product roadmap. The role requires enterprise stakeholder management, technical project delivery, and 20% customer travel.

Lead and close complex sell-side software and SaaS transactions, draft and negotiate MSAs, order forms and SOWs, advise Sales and Deal Desk on privacy, security, AI, IP and open source issues, partner with cross-functional stakeholders, improve templates and contracting processes, and provide practical legal guidance balancing risk and commercial objectives.

Leads pre-sales technical strategy for large enterprise accounts in high-tech and manufacturing. Partners with account executives and technical teams to drive Databricks evaluation, adoption, and expansion, especially for data, machine learning, and AI use cases. Builds executive relationships, establishes technical champions, leads virtual teams, presents business value, supports data-driven transformation, and mentors colleagues. Requires production programming experience and expertise in big data, data science, and cloud technologies.

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.

Customer-facing senior engineer who architects, builds, and productionizes end-to-end data and AI solutions on the Databricks platform. Leads design decisions, implements data pipelines, ML/AI model integration, and user-facing applications, contributes reusable assets, and collaborates cross-functionally to deliver measurable outcomes and operationalized deployments for enterprise clients.

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.

Customer-facing senior engineer who architects, builds, and productionizes end-to-end data and AI solutions on the Databricks platform. Leads architecture, implements data pipelines, ML/AI model integration, CI/CD deployments, and reusable accelerators while collaborating with customers and cross-functional teams to deliver measurable business outcomes.

Sell Databricks enterprise data and AI platform into a single strategic pharmaceutical account. Manage complex sales cycles, close incremental wins, expand customer vision with CIOs and LOB leaders, track opportunities in Salesforce, and exceed pipeline and revenue targets while ensuring customer satisfaction.

Manage and launch innovative learning programs globally, enhance user adoption, and leverage AI and data for effective enablement.

Lead the design, deployment, reliability, and evolution of global unified communications, enterprise voice, conferencing, AV, and workplace technology infrastructure. Support office expansions, executive environments, and large-scale deployments; troubleshoot complex communication systems; build automation and operational tooling; coordinate vendors and cross-functional teams; establish scalable standards and documentation; and mentor engineers.

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.