Member of Technical Staff

ThoughtSpot ThoughtSpot · Data AI · Bangalore, India

This role focuses on building and scaling SQL generation pipelines to transform raw information into actionable intelligence. It involves developing backend systems, improving query accuracy and performance, and incorporating AI/ML and LLM trends into query generation solutions. The role requires strong software engineering skills, proficiency in Java and SQL, and experience with distributed systems and AWS.

What you'd actually do

  1. Development of complex projects in Java, PostgreSQL, SQS, DynamoDB
  2. Design and implement scalable backend systems that process and manage large volumes of customer data
  3. Build and improve SQL generation pipelines that translate user intent into accurate, optimised queries across diverse data sources
  4. Analyse and improve the efficiency, scalability, and reliability of our backend stack
  5. Write robust code and write functional, performance, and system test suites

Skills

Required

  • 4+ years of professional experience in software engineering
  • Strong background in data science, analytics engineering, or a related quantitative discipline
  • Proficiency in Java and object-oriented programming principles
  • Deep understanding of SQL — query construction, optimisation, and execution across relational databases
  • Hands-on experience building or working with analytics tools, BI platforms, or query engines
  • Experience building distributed and scalable systems
  • Awareness of message queuing systems
  • Strong grasp of software engineering best practices
  • Excellent problem-solving skills and ability to troubleshoot complex issues
  • Ability to work independently and as part of a team
  • AI literacy and workflow integration
  • integrate artificial intelligence into their daily workflow
  • leverage AI tools (industry-leading LLMs) to increase productivity
  • using AI for research, content creation, and document summarization
  • write effective prompts to get the most accurate and creative results from AI tools
  • 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

Nice to have

  • Experience with NLP, LLMs, or AI-driven query generation systems
  • Familiarity with query plan analysis and database internals
  • Prior exposure to semantic layers, data modelling, or metadata management
  • Experience working on cloud platforms like AWS
  • Knowledge of agile development methodologies
  • Experience with Dropwizard for building RESTful APIs
  • Familiarity with DuckDB for analytical queries

What the JD emphasized

  • AI literacy and workflow integration
  • integrate artificial intelligence into their daily workflow
  • leverage AI tools (industry-leading LLMs) to increase productivity
  • using AI for research, content creation, and document summarization
  • write effective prompts to get the most accurate and creative results from AI tools
  • 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
  • AI Mindset for All Spotters
  • expected to be fluent and comfortable with using AI to do their best work
  • experiment with ThoughtSpot’s AI tools (like Spotter and SpotterViz) and leading industry LLMs to streamline workflows, enhance output, and uncover new insights
  • AI is a daily partner