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Bengaluru, Karnataka, India
Hybrid
About the role:
As a Staff Engineer on the Data Modelling team at ThoughtSpot, you will lead the design and evolution of core modelling that powers analytics experiences at scale. You will work on systems that simplify how enterprise data is modelled, governed, and consumed across large and complex deployments.
This is a hands-on technical leadership role focused on building scalable platform capabilities across semantic modelling, metadata management, governance, and analytics infrastructure.
What you'll do:
Design and build scalable backend services powering data modelling and metadata workflows.
Drive architecture for semantic modelling, metadata management, and analytics platform capabilities.
Build systems that simplify modelling workflows across large-scale enterprise deployments.
Improve scalability, reliability, and performance of modelling workflows.
Solve complex challenges around schema evolution, metadata consistency, governance, and scale.
Mentor engineers and drive engineering best practices across design, testing, and observability.
Collaborate closely with product and platform teams to deliver modelling capabilities end-to-end.
What you bring:
8+ years of experience building large-scale backend or platform systems.
Strong expertise in Java and distributed systems design.
Experience building metadata-driven platforms, semantic layers, or enterprise data systems.
Strong understanding of APIs, storage systems, and scalable backend architectures.
Experience working with relational or analytical data systems.
Strong debugging, problem-solving, and technical leadership skills.
Preferred Qualifications:
Experience with data modelling, semantic modelling, or analytics platforms.
Experience with relational databases such as MySQL or PostgreSQL.
Exposure to cloud and container platforms such as AWS,GCP, Docker, or Kubernetes.
Experience improving developer workflows, platform reliability, and operational scalability.
Exposure to agentic systems, AI-assisted analytics experiences, or LLM-powered workflows.
Familiarity with model context protocols (MCP), agent-to-agent communication patterns, or semantic retrieval systems is a plus.
Mandatory and Required Skills for All ThoughtSpot Roles
Spotters are expected to demonstrate AI literacy and workflow integration to include to ability to:
Comfortably and confidently integrate artificial intelligence into their daily workflow to increase productivity and quality.
Hands-on experience to leverage AI tools (industry-leading LLMs) to increase productivity, automate routine tasks, and improve work quality.
Speak to the experience of using AI for research, content creation, and document summarization while maintaining ownership of judgment and final decisions.
Write effective prompts to get the most accurate and creative results from AI tools.
Spotters are expected to exemplify these key traits and AI Mindset:
Curiosity in exploring new AI tools
Adaptability to quickly learn and implement new, emerging AI technologies
Critical thinking to know when to identify when AI should be used versus when human judgement is necessary
This combination of curiosity, adaptability, and discernment defines the AI mindset, and it’s required for every role at ThoughtSpot.
AI Mindset for All Spotters
At ThoughtSpot, we believe AI is a necessary and essential part of how we work. Every role, across every team, is expected to be fluent and comfortable with using AI to do their best work.
All Spotters are expected to experiment with ThoughtSpot’s AI tools (like Spotter and SpotterViz) and leading industry LLMs to streamline workflows, enhance output, and uncover new insights. Whether drafting content, analyzing data, or summarizing documents, AI is a daily partner. We value curiosity, openness to learning, and thoughtful application of AI to create real value. Training and resources are provided so every Spotter can confidently create with AI.
Hybrid Work at ThoughtSpot
Spotters are expected in-office 3 days per week to experience the energy of their local office. This approach balances the benefits of in-person collaboration and peer learning with the flexibility needed by individuals and teams.
ThoughtSpot for All
At ThoughtSpot, diverse teams build better products. Complex data problems need many perspectives, not just one. We welcome different backgrounds, identities, and experiences, and we work to create a place where everyone can be themselves and do their best work. If this role excites you and you believe you’re a strong match, we encourage you to apply.
What Makes ThoughtSpot a Great Place to Work?
ThoughtSpot is the Agentic Analytics Platform that empowers every enterprise to transform insights into action, on a mission to make the world more fact driven. 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 Trust, Customer Obsession, Innovation and Intensity, 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.
About ThoughtSpot
The world’s most innovative companies turn to ThoughtSpot’s AI-Powered Analytics to put data in the hands of everyone, from the C-suite to the frontline. With simple, natural language search and AI, anyone can ask questions, discover insights, and act with confidence. Unlike legacy tools that sacrifice performance for complexity, ThoughtSpot is intuitively designed for every business user while being built to handle the most complex, large-scale data, wherever it resides. This unique combination of speed and simplicity is why enterprise leaders trust ThoughtSpot to transform decision-making into a truly data-driven culture.
At ThoughtSpot, we’re a curious, data-driven bunch. We believe the world works better when everyone has access to facts. That’s why we build products that make asking and answering data questions as natural as having a conversation.