Jobs at Databricks

Design, build, and operate backend infrastructure for Databricks at scale. Develop cloud-agnostic systems, service platforms, and tooling to improve developer efficiency across languages and regions. Contribute across design, implementation, and operations for distributed, SaaS-oriented services.

Lead and grow a backend engineering team building scalable, cloud-agnostic infrastructure and services for big data and ML workloads. Hire engineers, enforce technical standards, partner with product and customers, define roadmap, and coordinate cross-team execution to deliver reliable, monitored, and tested systems at scale.

Design, implement, and optimize low-level application frameworks and core system infrastructure. Focus on JVM internals, memory, concurrency, performance tuning, and distributed systems. Mentor engineers, participate in architecture and code reviews, troubleshoot complex system issues, and improve scalability and reliability.

Lead GEO and AI search optimization to increase Databricks' visibility and citations across AI answer engines and organic search. Build experimentation programs, publish AI-citable technical content, maintain technical SEO health (schema, crawlability, Core Web Vitals), and partner cross-functionally to drive traffic, conversions, and pipeline while delivering executive reporting and a repeatable GEO playbook.

Serve as a senior pre-sales Solutions Architect for Databricks, driving technical engagements, proofs-of-concept, and customer adoption across Communications, Media, Entertainment & Gaming. Partner with Account Executives, influence stakeholders including C-level, coach junior architects, develop customer collateral, and lead workshops. Provide architecture, design, and technical strategy for cloud-based data analytics solutions and the Databricks platform.

Lead and grow a Developer Relations team for the Databricks Data + AI Platform. Own strategy, hiring, and advocacy; create scalable technical content, demos, and community programs; represent practitioners to product teams; speak at events; and apply AI to increase team leverage while maintaining technical depth.

Lead and grow a team of Developer Advocates to drive adoption of the Databricks Data+AI Platform. Set DevRel strategy, translate product roadmaps into developer-facing content, coach advocates, deliver talks and tutorials, run meetups and community programs, and collaborate with product and engineering to prioritize user-driven roadmap changes. Establish repeatable content and event playbooks and apply AI-assisted workflows to increase team leverage while maintaining technical depth.

Design and deploy production ML/AI architectures on the Databricks platform, lead Generative AI (LLM, RAG, agent) implementations, optimize and scale MLOps pipelines, provide technical pre-sales support, and translate customer feedback into product improvements while mentoring peers and meeting delivery milestones.

Own end-to-end customer relationships across Western Canada in Energy, Mining, and Utilities. Drive high-velocity face-to-face engagement with CIOs/CDOs, generate pipeline, move use cases from POC to production, architect account expansion plans, manage complex multi-stakeholder sales cycles, and maintain accurate Salesforce CRM hygiene and forecasting.

Lead and grow a team of open source Developer Advocates, deepen engagement with Apache and Linux Foundation communities, create technical content and events, align community needs with product and engineering, hire and develop advocates, and drive adoption and contribution across the Open Lakehouse stack and related open source projects.

Lead and grow a Developer Relations team focused on open source projects (Spark, Delta Lake, MLflow, Iceberg, Omnigent). Define strategy and success metrics, coach advocates, create high-quality technical content and events, engage with Apache/Linux Foundation communities, align community needs with product R&D, and drive external adoption and contributor growth.

Design and execute territory engagement strategies as a trusted technical advisor to drive adoption of the Lakebase product. Build demos, workshops, and customer collateral; architect transactional-to-lakehouse integrations; solve tier-3 technical issues; influence product roadmap with field insights; enable large-scale customer migrations, HA/DR, security and scalability across cloud platforms.

Lead technical strategy and pre-sales efforts for large enterprise accounts, driving Databricks adoption for ML/AI and data transformation. Act as main technical voice, build executive relationships and internal champions, mentor team members, and align technical solutions to business outcomes.

Serve as the primary technical pre-sales lead for large enterprise accounts, defining technical strategy, driving Databricks adoption for ML/AI, building technical champions, mentoring team members, and aligning solutions to business outcomes.

The Strategic Account Executive will manage enterprise accounts, driving revenue growth, developing strategies, and influencing decision-making with customer leadership.

Sell Databricks' cloud data platform to Financial Services accounts by building and expanding customer relationships, meeting CIOs and executives, closing new and existing accounts, managing pipelines and forecasts in Salesforce, exceeding revenue targets, identifying quick wins and long sales cycles, and coordinating internal and external success plans.

The Enterprise Account Executive will drive sales in Financial Services, managing both new and existing accounts, and exceeding revenue targets using a solution-based approach.

Develop and manage strategic sales in the financial services sector, exceeding revenue targets and ensuring customer satisfaction while articulating technology solutions to key decision-makers.

Sell Databricks enterprise cloud data platform to Financial Services accounts. Manage full sales cycle with CIOs and IT/LOB execs, grow existing accounts, close new business, meet pipeline and revenue targets, track activity in Salesforce, and promote value of Spark and Databricks solutions.

Lead delivery and hiring for Profile Agents within CustomerLake, building agent-driven pipelines, identity/entity resolution, and production Customer360 outputs. Define product/architecture, ensure reliability and governance, work with customers, and scale the team and platform.