Senior Data Engineer

Envoy protects the places the world relies on most by unifying people, spaces, and communications in one secure, integrated workplace management platform and ecosystem. More than 16,000 workplaces around the world trust Envoy to run secure, compliant, and connected operations across every location.

From manufacturing sites and data centers to life sciences labs, healthcare facilities, and corporate headquarters, Envoy unifies visitor management, risk assessment, mailroom management, digital signage software, resource booking, and emergency management into one integrated platform.

With deep integrations across access control, identity, compliance screening, and collaboration tools—including LenelS2, Brivo, Genetec, Honeywell, Cisco Meraki, Okta, Microsoft Azure, Microsoft Teams, Slack, ServiceNow, DocuSign, Avigilon Alta, and Descartes Visual Compliance—Envoy helps organizations reduce risk, stay audit-ready, and operate with clarity at scale.

Learn more at envoy.com

Envoy is the workplace platform that helps companies of every size manage their people, places, and visitors. Thousands of organizations — from startups to the Fortune 500 — rely on Envoy to bring people back to the office, deliver great in-person experiences, and turn the workplace into a strategic advantage. Behind the product is a fast-moving, AI-forward Data team that powers decision-making across Customer Success, Revenue Operations, Sales, Product, and Finance.

This role is based in our San Francisco office on a hybrid schedule (4–5 days in-office per week).

We are hiring a Senior Data Engineer to join Envoy’s Data team and help us scale the next generation of our analytics and AI infrastructure. This is a high-leverage role at the intersection of data modeling, AI tooling, and business impact. You’ll work directly with leaders across Customer Success, Revenue, Product, and Finance — turning ambiguous business questions into trustworthy data products that ship into Slack, Sigma, executive newsletters, and AI agents.

Our stack includes Redshift, dbt (900+ models), Sigma, Airflow, and Databricks, plus a growing portfolio of internal AI tools — most notably Claude-powered MCP servers backed by AWS Lambda that exposes our analytics warehouse to natural-language querying. We are actively evolving MCPs into a governed semantic layer, and this hire will be central to that effort.

• Own and extend our dbt warehouse (900+ models on Redshift), including dimensional modeling, snapshot strategy, macros, tests, and lineage hygiene. Help us reduce orphan models and tighten governance.

• Build and operate AI-native analytics tools. Contribute to AI and our broader MCP-based connector ecosystem (Lambda, API Gateway, Redshift Data API). Add new schemas, design persona-aware prompt templates, and improve tool reliability.

• Design a governed semantic layer. Help define canonical metrics in YAML (MetricFlow-compatible), align them with dimensional models, and ensure a single source of truth for ARR, NPS, retention, churn, and product engagement metrics.

• Build and maintain metrics APIs on AWS Lambda + API Gateway that power dashboards, AI agents, and recurring executive outputs (e.g., “The Envoy Gazette,” “The Envoy Herald”).

• Partner with stakeholders across Customer Success, Revenue Ops, Sales Enablement, Product, and Finance — translating fuzzy questions into models, dashboards, and AI workflows that get used.

• Drive analyses that move the business. Examples from the last quarter: closed-won bookings analyses, churn root-cause investigations, pricing/discount pattern analysis across Chorus call transcripts, customer account deep-dives, and Jira ticket deduplication.

• Build new ingestion pipelines (e.g., G2 reviews into Databricks following the Chargebee events pattern) and integrate new sources from Salesforce, Intercom, Jira, Chorus, Chargebee, and Ashby.

• Champion AI in your workflow. Use Claude Code, Codex, and Claude in Chrome to ship faster — while staying skeptical, validating grain, and verifying logic before anything reaches a stakeholder.

• 5+ years of experience in analytics engineering, data engineering, or BI engineering, with at least 2 years operating a production dbt project.

• Advanced SQL skills (window functions, CTEs, performance tuning) on a cloud warehouse — Redshift, Snowflake, BigQuery, or Databricks.

• Strong dimensional modeling fundamentals (star/snowflake, slowly changing dimensions, grain discipline) and a clear point of view on data governance and metric drift.

• Working proficiency in Python for data work — cleaning, transformation, scripting, and lightweight services (e.g., AWS Lambda).

• Hands-on experience with at least one modern BI tool (Sigma, Looker, Omni, Mode, Tableau).

• Demonstrated AI fluency: you actively use AI coding assistants in your workflow and can articulate where they help, where they hurt, and how you validate their output.

• Strong written and verbal communication — you can explain a model, a metric, or a tradeoff to a non-technical executive without losing precision.

• High agency. You find problems before tickets land in your queue and ship work end-to-end.

• Experience building or maintaining a semantic layer (dbt Semantic Layer, MetricFlow, Cube, LookML, etc.).

• Experience with MCP servers, LLM tool-calling, prompt engineering for analytics, or building AI agents over a warehouse.

• AWS infrastructure experience (Lambda, API Gateway, IAM, Terraform).

• Experience with Databricks, Airflow, or another orchestration layer.

• Background supporting Customer Success, Revenue Operations, or Finance teams in a B2B SaaS environment.

• Familiarity with vector search and Redshift ML or similar in-warehouse ML capabilities.

• You’ll have direct ownership of one of Envoy’s most-used internal AI surfaces and shape how the rest of the company interacts with data.

• You’ll partner closely with senior leaders, including the CFO/COO, on outputs that land in their inboxes and decisions.

• You’ll work on a small, output-oriented team that values fast iteration and craft — the kind of team where shipping a Lambda before lunch and refactoring a dbt model after is a normal day.

• You’ll get to define what “analytics engineering in the AI era” looks like at Envoy.

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