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Director of engineering • santa clara ca
- Promoted
- New!
Director of Engineering
ThoughtSpotMountain View, California, United States- Promoted
Director of Engineering
EbaySan Jose, CA, US- Promoted
Director of Engineering (Worklist)
AledadeSan Jose, CA, US- Promoted
- New!
Director of Blockchain Engineering
ConfidentialSan Jose, CA, United States- Promoted
Director of Engineering, Security
CoupangMountain View, CA, United States- Promoted
- New!
Director of Product Engineering
ASAPPMountain View, California, United States- Promoted
Director of Engineering
WatlowSan Jose, CA, United StatesDirector of Engineering
Cushman & WakefieldSunnyvale, CA, United States- Promoted
Director Of Engineering
KognitosSan Jose, CA, USDirector of Engineering
VirtualVocationsSanta Clara, California, United States- Promoted
Sr. Director of Engineering - Ads AI
LinkedInMountain View, CA, USDirector of Engineering
eBay Inc.San Jose, CA, United States- Promoted
- New!
Director of Engineering
ThalamusMountain View, California, United StatesDirector of Product Engineering
AsappMountain View, California, USADirector of Engineering, Growth Engineering Marketing Data Platform
CoupandMountain View, California, USADirector of Engineering
Millennium Hotel and ResortsSunnyvale, CA, US- Promoted
- New!
Director of Engineering
CerebrasMountain View, California, United States- Promoted
- New!
Director of Engineering
eBaySan Jose, California, United States- Promoted
Director Of Engineering
Columbia HospitalitySan Jose, California, United StatesThe average salary range is between $ 153,327 and $ 236,900 year , with the average salary hovering around $ 190,000 year .
- general dentist (from $ 182,063 to $ 250,000 year)
- engineering director (from $ 164,115 to $ 238,917 year)
- product director (from $ 170,327 to $ 237,736 year)
- director of engineering (from $ 153,327 to $ 236,900 year)
- planning engineer (from $ 123,773 to $ 236,343 year)
- technical director (from $ 131,250 to $ 235,000 year)
- software architect (from $ 167,558 to $ 231,450 year)
- product management (from $ 145,000 to $ 230,849 year)
- software engineering manager (from $ 175,500 to $ 229,381 year)
- audio engineering (from $ 175,500 to $ 228,100 year)
- Hayward, CA (from $ 212,500 to $ 247,000 year)
- Santa Clarita, CA (from $ 154,729 to $ 237,110 year)
- Santa Clara, CA (from $ 153,327 to $ 236,900 year)
- San Mateo, CA (from $ 131,776 to $ 234,277 year)
- San Jose, CA (from $ 130,143 to $ 233,500 year)
- Cedar Rapids, IA (from $ 118,750 to $ 232,500 year)
- San Diego, CA (from $ 131,519 to $ 232,458 year)
- Sunnyvale, CA (from $ 189,798 to $ 232,200 year)
- College Station, TX (from $ 136,435 to $ 230,000 year)
- San Francisco, CA (from $ 139,643 to $ 229,967 year)
The average salary range is between $ 120,250 and $ 209,994 year , with the average salary hovering around $ 165,000 year .
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Director of Engineering
ThoughtSpotMountain View, California, United States- Full-time
Director of Engineering
ThoughtSpot is seeking a dynamic Engineering Leader to lead the vision, strategy, and execution of Analyst Studio, our AI-powered data preparation and semantic modeling platform. This critical leadership role will oversee a multidisciplinary engineering team focused on building intelligent data transformation tools, semantic layer abstractions, and machine‑learning-driven metadata enrichment. Your work will empower enterprises to unify and operationalize data across sources with speed and trust. You will work closely with Product, UX, and Go‑To‑Market teams to deliver next‑generation capabilities in structured data transformation, natural language‑to‑SQL translation, and knowledge‑graph‑powered context modeling. We’re looking for someone with deep expertise in the data domain, whether in analytics or related areas that emphasize scalable architectures. Experience in search, AI / ML, or enterprise SaaS is highly valuable.
Responsibilities
Drive Technical Vision & Strategy : shape the future of ThoughtSpot’s Analyst Studio
Lead and Scale Engineering Team : lead, mentor, and grow a high‑performing team of backend, ML / AI, and frontend engineers
Architect for Scale : oversee scalable system design for semantic layers, data pipelines, and AI / LLM‑driven transformation services
Innovate in AI & Analytics : guide implementation of LLM‑based data enrichment, automated data profiling, tagging, and ontology mapping
Build for high quality : champion best practices in reliability, security, testing, and observability
Ensure Security & Compliance : drive best practices for cloud security, data privacy, and compliance with industry standards
Collaboration & Stakeholder Management : work closely with cross‑functional teams, including product, UX, and customer success, to align technical goals with business objectives
Foster a High‑Performance Culture : attract, retain, and mentor top‑tier engineering talent
Required Skills / Qualifications
12+ years of total engineering experience, including 5+ years in engineering leadership roles
Proven experience leading teams delivering high‑performance enterprise software or data platforms
Strong understanding of semantic layers, data modeling, and data preparation workflows
Familiarity with modern data stack tools (e.g., dbt, Cube.dev, AtScale, Trino, Airflow)
Hands‑on experience with LLMs, embedding models, or knowledge graphs is a strong plus
Track record of building and scaling distributed, production‑grade software systems
Expected to be hands‑on, capable of diving deep into debugging customer issues, analyzing logs and code, and resolving complex technical challenges
Experience integrating LLM‑driven agents or natural language interfaces with enterprise data systems is a plus
Background in analytics, BI, metadata management, or MDM solutions is preferred
Understanding of cloud infrastructure (AWS / GCP), containerization, and CI / CD pipelines
Strong communication and executive presence; able to influence cross‑functional leadership
Familiarity with geographically distributed teams and infrastructure, ideally in a high‑release‑velocity or startup environment
Who You Are
Technical – you love technology, building, using, and staying abreast of the latest developments
Problem solver – inspirational in problem‑solving, algorithmic thinking, and programming skills with computer science fundamentals
Recruiter & team builder – always looking for & hiring top talent, mentoring, and making others better
Platform builder – dedicated to building large‑scale HA infrastructure that supports search applications
Customer obsessed – you build software with customers in mind and aim for happy customers
What makes ThoughtSpot a great place to work?
ThoughtSpot is the experience layer of the modern data stack, leading the industry with our AI‑powered analytics and natural language search. We hire people with unique identities, backgrounds, and perspectives—this balance‑for‑the‑better philosophy is key to our success. When paired with our culture of Selfless Excellence and our drive for continuous improvement (2% done), ThoughtSpot cultivates a respectful culture that pushes norms to create world‑class products. If you’re excited by the opportunity to work with some of the brightest minds in the business and make your mark on a truly innovative company, we invite you to read more about our mission, and apply to the role that’s right for you.
ThoughtSpot for All
Building a diverse and inclusive team isn’t just the right thing to do for our people, it’s the right thing to do for our business. We know we can’t solve complex data problems with a single perspective. It takes many voices, experiences, and areas of expertise to deliver the innovative solutions our customers need. At ThoughtSpot, we continually celebrate the diverse communities that individuals cultivate to empower every Spotter to bring their whole authentic self to work. We’re committed to being real and continuously learning when it comes to equality, equity, and creating space for underrepresented groups to thrive. Research shows that in order to apply for a job, women feel they need to meet 100% of the criteria while men usually apply after meeting 60%. Regardless of how you identify, if you believe you can do the job and are a good match, we encourage you to apply.
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