Cssmerge Engineering Manager to lead the evolution from traditional analytics to a next-generation intelligence platform. Responsible for managing data pipelines, semantic layers, and delivering customer-facing analytics products.
Responsibilities
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.
Qualification
Blended Team LeadershipCross-Functional Team BuildingModern Data ModelingPragmatic Data GovernanceProduct & Executive PartnershipFull-Stack AccountabilityForward-Looking MindsetDesirable Technical SkillsData Platform & Analytics EngineeringHands-on experience with SQLMeshPipeline CI/CDClickHouse
Required
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
Preferred
Restaurant, marketplace, or delivery analytics.
Familiarity with Otter Business Manager is a plus.
