Top Tech Jobs & Startup Jobs in NYC, NY

Lead design for a 0-to-1 agent-driven AI product that makes Lakehouse data actionable. Define workflows, conduct user research, collaborate with PM and engineering, create intuitive visual and interaction designs, and mentor junior designers.

Develop and manage the research infrastructure for AI at Databricks, focusing on large-scale training, orchestration, and improving developer productivity.

Drive net-new enterprise sales of Databricks’ cloud data platform to digital-native accounts. Develop account strategies, engage buying centers, identify use cases, communicate technical and business value, orchestrate internal teams, negotiate, and close deals. The role requires SaaS, PaaS, cloud, or big data sales experience, executive customer relationships, quota achievement, and success winning new business.

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%.

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.

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.

Leads partner technical enablement and platform adoption for Customer Lake and Lakewatch. Co-architects enterprise data solutions, expands observability deployments, advises partner executives, creates reusable architectures and deployment blueprints, and coordinates cross-functional go-to-market initiatives. The role requires advanced coding, data architecture, Databricks, cloud, data governance, monitoring, and executive influence expertise, with responsibility for driving consumption growth and competitive enterprise wins.

Drive enterprise adoption of Databricks Genie by achieving consumption, bookings, and activation goals. Build executive-backed opportunities, develop repeatable field plays, enable account teams, and coordinate sales, solutions architecture, business units, and partners. Translate customer and market feedback into product and go-to-market recommendations while expanding production deployments. The role requires enterprise software sales or consulting experience in BI, analytics, data platforms, embedded analytics, or business-facing AI, along with complex buying-center navigation, value selling, land-and-expand execution, and partner strategy development.