Sr. Business Intelligence Engineer, Enterprise Intelligence (hybrid, Bangalore)

Smartsheet Smartsheet · Seattle · India · Business Intelligence & Ops

Senior Business Intelligence Engineer to build and govern a new Enterprise Insights & Intelligence team. The role involves automating executive reporting, standardizing metrics, and enabling self-serve and AI-powered data solutions. Key responsibilities include designing governed metric models, owning corporate scorecards with AI anomaly detection, leading metric governance, building AI agent integrations for natural language querying of enterprise data, and driving self-serve analytics enablement.

What you'd actually do

  1. Design, build, and maintain governed metric models — standardised, reusable definitions of business KPIs that dashboards, reports, and AI agents all query from a single source of truth
  2. Own the automation and maintenance of corporate scorecards and executive reporting (SLT/XLT), ensuring trusted, timely data with AI-powered anomaly detection and alerting
  3. Build AI agent integrations (MCP servers, skills, subagents) that allow tools like Claude and Snowflake Cortex to query enterprise data through the semantic layer with metric-correct SQL
  4. Lead metric certification and governance — maintain a centralised KPI glossary, standardise dashboards, and retire stale reporting assets
  5. Drive self-serve analytics enablement — documentation, training, dashboard quality checks, and experimentation governance across Amplitude, Tableau, and other platforms

Skills

Required

  • 5+ years of experience in analytics engineering, BI engineering, data engineering, or a closely related role
  • Experience with KPI design and insight generation
  • Deep SQL expertise
  • Experience working in cloud data platforms such as Snowflake and/or Databricks
  • Experience building semantic layers, governed data models, or canonical metric definitions for downstream consumption
  • Working familiarity with AI/LLM tooling — concepts such as MCP (Model Context Protocol), agentic frameworks, or tool-use patterns for large language models
  • Proficiency with one or more BI/visualisation tools (Tableau, Amplitude, or similar)
  • Strong cross-functional collaboration skills
  • Excellent async communication across time zones
  • A proactive, ownership-driven mindset

Nice to have

  • Experience building AI agent skills, subagents, or MCP server integrations for LLMs
  • Hands-on experience using agentic coding platforms (Claude Code, Cursor, Windsurf, etc.) to streamline and automate analytics workflows
  • Software engineering experience (Python, JavaScript/TypeScript)
  • Experience with event taxonomy design, behavioural analytics pipelines, or product instrumentation (Amplitude, Segment, etc.)
  • Familiarity with metric governance frameworks, data catalogues, or data quality tooling
  • Prior experience working in a SaaS or enterprise software environment
  • dbt (dbt Core or dbt Cloud) and concepts like YAML-based metric definitions and reusable data models

What the JD emphasized

  • build this function from the ground up
  • foundational hire
  • greenfield environment
  • AI agent integrations
  • governed metric models
  • trusted, consistent, accessible

Other signals

  • building foundational function
  • establishing new team
  • greenfield environment
  • AI agent integrations
  • governed data layer