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About the Delivery Engineer Team

As a member of the Go-To-Market Delivery Engineer team, you will own the post-sales onboarding and data health for customers. Your goal will be to drive data trust, help embed Mixpanel into our customers' data stack, and deliver on emerging AI integrations - delivering on the full value of Mixpanel as a self-serve analytics platform. You will work and consult with GTM team members and a diverse array of customers to successfully roll out product analytics to their organization and execute on technical projects and services that delight our customers.

About the Role

As a Delivery Engineer III, you will be on the front lines with our clients as they integrate Mixpanel into their core product development processes. You will lay the foundation for customers to adopt product analytics and get value from Mixpanel by delivering a world-class, on-time, and value-oriented onboarding experience. With your comprehensive project management knowledge, consultative approach, expertise in the analytics space, and technical knowledge of the modern data stack, you will lead our clients' first experience with Mixpanel as they incorporate product analytics into their data ecosystem as a foundational element. With your deep technical breadth and expertise in the analytics space, you'll be the expert consultant on all things data and ecosystem. As Mixpanel and our customers continue to iterate on agentic integrations, you'll own ensuring customers are able to build, assemble context, and integrate AI workflows with Mixpanel.

Responsibilities

• Own onboarding and data health for our strategic and high-value clients, including ongoing enhancements to their data quality and overall tech stack integration
• Align with pre-sales teams and consult with prospects/clients to define business goals and metrics to guide data architecture and project outcomes
• Engage with customers' engineering, product management, and marketing teams to handle technical onboarding, optimize Mixpanel deployments, and improve data trust
• Deliver a variety of technical services ranging from data architecture consultations to adoption and change management best practices
• Leverage modern data architecture expertise to create scalable data governance practices and data trust for our customers, including data optimization and re-implementation projects
• Successfully execute on deliverables whilst balancing project timelines, scope creep, and unanticipated issues
• Collaborate with our technical and solutions partners as needed on data optimization and onboarding projects
• Be a technical sponsor for internal engagements with Mixpanel product and engineering teams to prioritize product and systems tasks from clients
• Build AI automations to help customers manage their data at scale
• Consult with customers on integrating their agentic workflows with Mixpanel data.

We're Looking For Someone Who Is:

• Comfortable with data querying, modeling, and transforming in at least one core tool, including SQL / dbt / Python / Business Intelligence tools / Product Analytics tools, etc.
• Familiar with databases and cloud data warehouses like Google Cloud, Amazon Redshift, Microsoft Azure, etc.
• Familiar with product analytics implementation methods like SDKs, Customer Data Platforms (CDPs), Event Streaming, Reverse ETL, etc.
• Familiar with analytics best practices across business segments and verticals
• Can manage complex projects with assorted client stakeholders, working across teams and departments to execute real change while managing scope and timelines
• Has embedded AI into their workflows and is familiar with using MCP servers, building new skills, setting context, and can credibly consult with our customers about their AI/data strategy
• Has experience in customer success, client-facing professional services, consulting, or technical project management role
• Excellent written, analytical, and communication skills
• Strong process and/or project delivery discipline
• Eager to learn new technologies and adapt to evolving customer needs

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