Smartsheet - Sr. Business Intelligence Engineer, Enterprise Intelligence (Hybrid, Bangalore)
Requirements
• Bachelor's degree (B.Tech / B.E. / B.Sc.) in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field • 5+ years of experience in analytics engineering, BI engineering, data engineering, or a closely related role • Experience with KPI design and insight generation — ability to define meaningful metrics, analyse trends, identify anomalies, and communicate findings that drive business decisions • KPI design and insight generation • Familiarity with dbt (dbt Core or dbt Cloud) and concepts like YAML-based metric definitions and reusable data models; hands-on experience is a plus but not required • Deep SQL expertise with experience working in cloud data platforms such as Snowflake and/or Databricks • cloud data platforms • Experience building semantic layers, governed data models, or canonical metric definitions for downstream consumption • semantic layers • Working familiarity with AI/LLM tooling — concepts such as MCP (Model Context Protocol), agentic frameworks, or tool-use patterns for large language models • AI/LLM tooling • Proficiency with one or more BI/visualisation tools (Tableau, Amplitude, or similar) • BI/visualisation tools • Strong cross-functional collaboration skills and excellent async communication across time zones (IST / US Pacific overlap expected) • A proactive, ownership-driven mindset — comfortable building new processes and standards in a greenfield environment • Experience building AI agent skills, subagents, or MCP server integrations for LLMs • AI agent skills, subagents, or MCP server integrations • Hands-on experience using agentic coding platforms (Claude Code, Cursor, Windsurf, etc.) to streamline and automate analytics workflows • agentic coding platforms • Software engineering experience (Python, JavaScript/TypeScript) with the ability to contribute to application-level instrumentation code • Python, JavaScript/TypeScript • Experience with event taxonomy design, behavioural analytics pipelines, or product instrumentation (Amplitude, Segment, etc.) • event taxonomy design • Familiarity with metric governance frameworks, data catalogues, or data quality tooling • metric governance frameworks • Prior experience working in a SaaS or enterprise software environment • SaaS or enterprise software • Get to Know Us: • Get to Know Us: • At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.
Responsibilities
• 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 • governed metric models • Own the automation and maintenance of corporate scorecards and executive reporting (SLT/XLT), ensuring trusted, timely data with AI-powered anomaly detection and alerting • automation and maintenance of corporate scorecards • Conduct deep dives on key KPIs and company goals, surfacing actionable insights and translating short- and long-term business priorities into data-driven recommendations shared via reviews and async updates • deep dives on key KPIs and company goals • Lead metric certification and governance — maintain a centralised KPI glossary, standardise dashboards, and retire stale reporting assets • metric certification and governance • 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 • AI agent integrations • Drive self-serve analytics enablement — documentation, training, dashboard quality checks, and experimentation governance across Amplitude, Tableau, and other platforms • self-serve analytics enablement • Partner with Product, Engineering, Finance, GTM, and Customer Success to align metric definitions and data sources cross-functionally • Product, Engineering, Finance, GTM, and Customer Success • Translate qualitative UX signals and customer feedback into measurable data pipelines • UX signals and customer feedback
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