Jobs at Databricks

Serve as the COO and strategy partner for Databricks’ India go-to-market team. Develop GTM plans, run sales operating cadences, manage forecasting and business reviews, model territories and quotas, analyze datasets, and create dashboards and scorecards. Drive cross-functional alignment, process optimization, accountability, and strategic initiatives across APJ while translating leadership goals into executable plans and measurable outcomes.

Owns end-to-end European payroll operations, compliance, audits, controls, equity and RSU payroll processing, reconciliations, vendor performance, and payroll technology improvements. Leads a team of payroll professionals, partners with HR, Finance, Legal, Tax, and Stock Administration, resolves escalations, ensures accurate and timely payroll delivery, and provides metrics and variance analysis to leadership.

Serve as a strategic People Partner to corporate-function leaders, translating people strategy into business outcomes. Own performance, compensation, talent review, culture, and organizational programs; provide organizational insights using people data; coach VP and executive leaders; support organizational change, talent strategy, and leadership effectiveness; and develop AI-enabled workflows and scalable people analytics solutions.

Owns customer-facing FDE engagements from executive discovery and value definition through MVP scoping, PRD creation, agile delivery, launch, adoption, and strategic handoff. Partners with sales and engineering, manages backlogs and stakeholder communications, resolves technical and political blockers, validates business value, and identifies follow-on opportunities.

Enterprise Account Executive responsible for expanding Databricks’ footprint with existing customers, converting prospects, driving platform consumption, and closing strategic committed deals. Duties include prospecting, account and territory planning, pipeline management in Salesforce, proof-of-concept development, executive engagement, and coordinating with technical and customer success teams. The role requires enterprise technology sales experience, strong prospecting and engagement skills, technical understanding of data and AI platforms, and travel of up to 50%.

Leads end-to-end development of full-stack web and mobile applications, data pipelines, AI-powered integrations, authentication systems, and deployment automation for internal employee experience tools. Owns architecture, implementation, reliability, stakeholder management, roadmap planning, and technical documentation. Mentors engineers, establishes software development standards, and collaborates with Security, Legal, HR, Finance, and Engineering 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.

Lead technical strategy for customer accounts, from discovery through production deployment and platform adoption. Design scalable solutions across data engineering, machine learning, AI, streaming, and real-time analytics. Advise senior customer architects and engineering leaders, lead architecture discussions, build custom demonstrations, coordinate cross-functional resources, and influence product direction. The role requires strong Python and SQL coding, distributed data systems expertise, public-cloud deployment experience, and the ability to translate technical architectures into business value.

Lead technical strategy for customer accounts by designing production-grade data, AI, streaming, and analytics architectures. Advise senior technical stakeholders, drive Databricks adoption and consumption, demonstrate competitive differentiation, orchestrate cross-functional resources, and provide product feedback. The role requires strong Python and SQL skills, distributed data systems expertise, public cloud deployment experience, and the ability to communicate technical solutions to technical and executive audiences.

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.

Manage strategic enterprise accounts across the Middle East and Africa, develop territory strategies, exceed revenue targets, and close new business. The role involves prospecting, stakeholder mapping, value selling, executive engagement, Salesforce forecasting, identifying expansion opportunities, promoting Databricks’ Data Intelligence Platform, coordinating field engineering resources, and negotiating with technical and C-suite buyers.

Build and productionize customer data and AI solutions on the Databricks platform. Own architecture and design decisions while delivering end-to-end data pipelines, applications, and ML/AI integrations. Lead technical projects, advise enterprise stakeholders, integrate customer systems, provide training, and ensure scalable, secure production deployments. Collaborate with engineering, product, support, and project teams while contributing reusable frameworks and influencing the product roadmap.

Lead strategic enterprise sales for Databricks’ Data Intelligence Platform. Develop account and partner strategies, identify big data and AI use cases, build executive relationships, drive adoption of usage-based services, coordinate technical and professional services teams, and exceed booking and usage targets. The role requires enterprise software sales experience, knowledge of data and AI technologies, complex regulated-account experience, cloud co-selling expertise, and fluent Spanish and business English.

Leads architecture and hands-on development of production agentic applications for quote-to-cash workflows. Builds reliable LLM-powered agents, evaluation systems, human-in-the-loop controls, governed tool integrations, and auditability for pricing, ordering, billing, and revenue recognition. Partners with Finance, Deal Desk, Sales, Legal, and engineering teams to migrate enterprise workflows, protect financial integrity, establish agentic engineering standards, and mentor engineers. This is a senior technical leadership role without people-management responsibility.

Own the non-technical lifecycle of Forward Deployed Engineering engagements, from executive discovery and value scoping through MVP definition, PRD creation, agile delivery, launch, adoption, and strategic handoff. Partner with sales and engineering, manage stakeholders and escalations, prioritize backlogs, validate solutions, document outcomes, and identify future engagement opportunities.

Hunt for new enterprise and digital-native customers across Spain and Portugal, develop territory strategies, exceed sales quotas, identify data and AI use cases, and sell Databricks’ cloud data platform through solution-based, business-outcome-focused sales. Build relationships with customers, partners, and internal teams while articulating complex cloud and big data technologies and their business value.

Design and build scalable backend services and APIs for Databricks’ MLOps and LLMOps platform. Develop systems for ingesting, storing, and querying AI traces, metrics, and artifacts; create evaluation and monitoring capabilities; optimize platform scalability and cost; and establish engineering best practices. Collaborate with product, research, and customers while mentoring engineers and taking systems from design through production.

Lead the Bengaluru AI engineering team in defining strategy and architecture for Databricks’ MLOps and LLMOps platform. Design and deliver reliable, scalable systems for AI experiment tracking, model registry, trace and artifact management, agent evaluation, and developer experiences. Drive cross-functional technical alignment, mentor engineers, make architecture decisions, maintain hands-on development involvement, and represent the team through open-source contributions, talks, and technical writing.

Provides high-touch technical support for strategic Databricks customers. Manages critical support cases, coordinates Engineering, Product, SMEs, and account teams, drives issue resolution, identifies case trends, engages executives, leads customer roundtables, and promotes customer self-sufficiency. Requires strong project management, distributed big data problem-solving, application development experience, and professional Mandarin and English proficiency.

Build and improve Databricks platform features across backend, full-stack, infrastructure, databases, systems, cloud, and customer-facing products. Responsibilities include designing, developing, testing, and operating reliable, scalable, and secure software in production while collaborating with engineering teams and contributing throughout the full software development lifecycle.