Engineering Jobs

Vice President, Engineering Engagement — 2 Locations. Apply via Workday.

Sr. Data Engineer - Data Engineering 4B — 1401-GIPL: Prestige Technology Park IV, Bangalore. Apply via Workday.

AI Specialist, Executive Support Engineering — San Jose, CA. Apply via Workday.

MTS, AI Engineering, SMAI — 2 Locations. Apply via Workday.

Senior Manager, Engineering - R&D — Portage, Michigan. Apply via Workday.

Senior Manager, Field Applications Engineering — 2 Locations. Apply via Workday.

Staff Engineer, Package Development & Engineering — 2 Locations. Apply via Workday.

Senior Engineer, R&D Engineering Services & Labs — Fremont, California. Apply via Workday.

Vice President, Information Security Engineering — Arlington, Virginia. Apply via Workday.

Data Scientist, Innovation Engineering Technology — Taichung - Fab 16, Taiwan. Apply via Workday.

VP, Application Reliability & Operations Engineering — 5 Locations. Apply via Workday.

Manager, Software Development & Engineering (Mobile – Camera Experience) — 2 Locations. Apply via Workday.

Sr. Data Engineer - Data Engineering 4B — Uppal, STPI. Apply via Workday.

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Product Marketing, AI-Powered Data Engineering Intern Location: Menlo Park, California, United States At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake started as the place companies go to understand their data. Now we’re making it the place they put that data to work for AI. Our Data Engineering team builds the pipelines, platforms, and AI-driven solutions that power how Snowflake goes to market, from customer intelligence and launch readiness to the stories that bring our impact to life. We sit at the intersection of engineering, go-to-market strategy, and customer storytelling. As an intern on this team, you'll build

(GAQ427R231) About the role As Databricks scales at unprecedented velocity, how we invest our R&D capital—both human and compute—is critical to our scale. We are looking for a Product Finance leader to own R&D capital allocation and engineering operations. You will be a key finance partner to our senior Engineering and Product Operations leaders, with a mandate that spans product-level R&D ROI, global workforce and location strategy, and the rapidly evolving economics of AI-enabled software development. The impact you will have Drive product-level ROI and R&D capital allocation Establish frameworks to measure product-level ROI across a fast-moving platform like Databricks where engineering velocity is extremely high. Operationalize ROI metrics so they directly inform product investment and resource allocation decisions. Define engineering economics in the AI era Partner with Engineering to model how AI developer tooling and internal token spend scale alongside headcount, quantifying the tradeoff between human capital and compute capital. Measure the end-to-end cost of AI-enabled engineering, including the second-order impact on cloud spend, and partner with Engineering to optimize investments. Shape global workforce and location strategy Drive multi-year headcount planning across global engineering hubs, balancing cost per hire, talent density, and university recruiting pipelines. Partner closely with Workplace and Facilities leadership to synchronize R&D hiring roadmaps with global real estate strategy and multi-year CapEx planning. Scale R&D finance operations and build the team Bring systems-level thinking to R&D finance operations, building scalable, automated workflows across headcount management, PO planning, monthly accruals, and SOX audit compliance. Dogfood the Databricks platform to modernize internal finance tooling and deliver self-serve operational visibility to engineering leaders. Build, mentor, and scale a hi