Lead the AI/BI Dashboard team at Databricks, focusing on product growth and engineering management.
Posted by employer 2 days ago
First seen on Joblaze 1 day ago
Last verified on the company career page 10 hours ago
Skills & Technologies
What you'll build
Must have
Role intensity
10% coding — mostly leadership/strategy
AI in the day-to-day
Leveraging AI to change how users interact with and leverage our product.
Requirements
Not disclosed in this posting: work arrangement, visa sponsorship.
Joblaze summary
In this role, the Senior Engineering Manager will oversee the development of the AI/BI Dashboard product, focusing on enhancing user experience through efficient dashboard creation and data insights. The position requires expertise in full-stack and backend development, particularly with AI and LLM technologies, to ensure high performance and quality. Ideal candidates will have extensive experience managing engineering teams in a SaaS environment and a strong track record in talent acquisition and development. The team operates in a fast-paced environment, emphasizing collaboration across departments to achieve product goals.
Joblaze insights
Quick facts
From the original posting
RDQ427R365
At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
We are the “AI/BI” Dashboard team responsible for making Databricks the best product for business users to create, share and consume data insights. We own the entire product stack end-2-end: the Dashboard creation and consumption UI, the query and permissions layer, the control plane for the service, the consumption surface across web, mobile and Desktop as well as the distribution infrastructure across various channels (e-Mail, Mobile, Slack/Teams etc.). At every layer of our stack, we are leveraging AI to change how users interact with and leverage our product in completely new ways to find the answers they need quicker than ever before.
We're seeking a dedicated Senior Engineering Manager who will help grow the AI/BI Dashboard product and service platform. This means tackling a number of challenging fullstack and backend problem spaces, for example making agentic dashboard authoring and AI insights fast and performant while maintaining high quality, enabling the creation and consumption of Dashboards and BI features across the entire Databricks platform and scaling our service to the next order of magnitude of users. This role also requires experience in applying AI and LLM technology directly into the product surface and guiding the team to strike a balance between pushing up quality while maintaining performance and cost.
You will report directly to the Director of Engineering.
The main responsibilities include:
What we look for:
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
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