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Engineering Manager - Data Engineering & Insights

Otter
CompanyOtter
CategoryEngineering
LocationSeattle
RemoteOn-site (inferred)
EmploymentNot stated
LevelManager
SalaryNot stated by the employer
Posted4 Jun 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
Who we are  In the past, to be a successful restaurateur, you simply had to have a passion for food and a passion for people - but to succeed as a digital restaurateur you also need to have a passion for technology. We believe in the joy of serving others, and that's why we created Otter – to help restaurateurs succeed in online food delivery. Restaurants around the world, both large and small, including Chick-fil-A, Ben & Jerry’s, KFC, and Eataly trust our software to power their delivery business. We increase sales, reduce order issues, and decrease delivery headaches.    Role We are looking for a hands-on Engineering Manager to spearhead our evolution from traditional analytics to a next-generation intelligence platform. This is a great opportunity to lead a team managing the data behind roughly 80% of all online food orders in the US, and modernize our ecosystem by building an impeccable data foundation that moves beyond static charts into live, conversational insights. The Impact: Empower merchants with fast, trustworthy, and actionable metrics that change how they run their businesses every single day. What you’ll do Own Otter Insights End-to-End: Lead the strategy for everything inside Business Manager (pipelines and datasets to the semantic modeling layer and customer-facing embedded analytics). Manage Ingestion to Serving: Drive both real-time and batch pipelines, ensuring canonical datasets and robust APIs are built to empower other internal teams. Scale the Semantic Layer: Oversee frameworks (like Cube/SQLMesh) to ensure metrics and dimensions remain consistent across batch and real-time processing. Drive Data Governance: Establish analytics engineering standards and ensure adoption across broader product teams to maintain high data quality. Ship High-Performance Products: Deliver data-intensive, customer-facing applications including the Analytics App, Analytics Studio, automated reports, and data-sharing APIs. Deploy Safe AI Insights: Build automated AI insights on top of governed metrics, implementing strict guardrails, observability, and customer-impact triage. Build and Coach the Team: Hire, mentor, and retain a cross-functional team of analytics engineers and full-stack/frontend engineers while setting technical direction across the stack.   What we’re looking for Blended Team Leadership: 4+ years of experience leading engineering teams across both data/platform and product domains Cross-Functional Team Building: Proven track record building and scaling diverse teams (backend, analytics engineering, and full-stack/frontend) Modern Data Modeling: A strong background in data modeling and semantic layers, alongside a history of delivering B2B or customer-facing analytics products Pragmatic Data Governance: Experience implementing data lineage, catalogs, compliance, and quality frameworks Product & Executive Partnership: Ability to collaborate closely with PMs, designers, and executive stakeholders w Full-Stack Accountability: Comfort owning end-to-end operational health, monitoring incidents, and managing on-call rotations from the data pipeline down to the user interface. Forward-Looking Mindset: A genuine interest in establishing AI-ready data foundations and building AI-enabled insights on top of certified metrics and metadata.   Desirable Technical Skills Data Platform & Analytics Engineering Hands-on experience with SQLMesh, dbt, and Cube. Pipeline CI/CD, data observability, and orchestration (Flink / or similar batch tools) ClickHouse, Pinot, or Trino Data access controls, platform hardening, and permissioned sharing Applications & Insights (Full-Stack) Engineering experience across React, TypeScript, and Java (or Kotlin/Scala) Building dashboards, custom charts, automated report scheduling, and data exports Designing and implementing sec
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