Jobs at Databricks

Lead customer-facing technical engagements spanning discovery, solution design, architecture reviews, proofs of concept, and platform demonstrations. Build production-quality data solutions and reusable technical assets using Python, SQL, cloud platforms, distributed data systems, analytics, and machine learning technologies. Partner with Account Executives to develop account strategies, expand platform adoption, and communicate Databricks’ differentiation.

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.

Leads complex enterprise architecture engagements, technical and consumption strategy, executive customer relationships, platform adoption, competitive evaluations, and AI/data solutions. Serves as a Databricks technical authority, orchestrates cross-functional teams, mentors solutions architects, develops competitive strategies, and contributes to field engineering thought leadership. Responsibilities span enterprise migrations, real-time systems, lakehouse platforms, data governance, and AI/ML at scale.

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.

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.

Build customer relationships and demonstrate Databricks’ AI and data analytics platform through prototypes, demos, reference architectures, workshops, and technical guidance. Collaborate with Account Executives to drive adoption, advise customers on architecture and implementation, and develop expertise in data and AI solutions. This is an in-office role based in Chicago, Illinois.

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 complex enterprise customer engagements as a technical authority for Databricks data and AI solutions. Drives architecture, platform adoption, consumption strategy, competitive positioning, and executive relationships. Designs large-scale data, streaming, migration, governance, and AI/ML solutions; orchestrates cross-functional teams; mentors other solutions architects; and contributes to technical thought leadership. Requires advanced coding, enterprise data architecture expertise, Databricks proficiency, strategic account leadership, and executive communication.

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.

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.

Build and productionize data and AI solutions for federal government customers using Databricks. Lead architecture, design, and implementation of end-to-end data engineering, machine learning, and application systems. Deliver secure, scalable production architectures, integrate customer systems, guide technical projects, train customers, and collaborate with engineering, product, support, and customer stakeholders. Contribute reusable frameworks and accelerators while managing technical delivery and customer relationships.

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.

Lead and develop a team of Account Executives serving Commercial customers. Drive platform adoption, consumption growth, expansion, net retention, and workload discovery through strategic account planning and executive relationships. Coach sellers on value-based selling, cross-functional orchestration, upselling, churn mitigation, forecasting, and pipeline management. Translate technical architectures into measurable business outcomes and ROI while supporting high-impact expansion opportunities through occasional travel.

Leads AI/ML architecture strategy for customers, designing production-grade solutions involving RAG, agentic systems, guardrails, evaluation, and observability. Advises senior technical stakeholders, drives Databricks adoption and consumption, leads competitive technical engagements, coordinates cross-functional resources, and influences product direction. Requires strong Python and SQL skills, distributed data architecture expertise, public-cloud deployment experience, and willingness to travel up to 30%.

Drive enterprise sales growth for Databricks across Fortune 500 CMEG accounts. Build relationships with executives and decision-makers, expand platform adoption into new business units, exceed pipeline and revenue targets, manage forecasts in Salesforce, and use value-based selling to communicate the benefits of Databricks’ data and AI platform. The role requires enterprise sales expertise, technical fluency in big data, cloud, SaaS, analytics, and AI, and the ability to manage strategic accounts independently.

Drive enterprise SaaS sales for Databricks by prospecting, identifying buying centers, developing account strategies, communicating platform value, guiding negotiations, closing new accounts, and expanding existing relationships. The role requires consultative selling of cloud, big data, and AI technologies, engagement with CIOs and decision-makers, quota attainment, and collaboration across teams.

Manage strategic Fortune 500 and enterprise accounts for Databricks’ Data Intelligence Platform. Build executive relationships, drive value-based growth, expand usage across business units, exceed pipeline and revenue targets, forecast in Salesforce, and lead solution-based sales involving big data, cloud, SaaS, analytics, and AI.