Delivery Engineer II (GTM)

About this role

About Mixpanel

Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com .

About the GTM 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 II, you will be on the front lines with our clients as they integrate Mixpanel into their core product development processes. You'll own onboarding, implementation, and data health for a portfolio of primarily SMB and scaled accounts — using established playbooks, resources, and processes to solve customer problems and keep projects moving on-time and to scope. This role blends technical ownership of data-related outcomes with implementation. You're comfortable auditing and identifying opportunities for data quality improvements, while also driving structured onboarding work from kickoff to go-live (typically a 30–90 day lifecycle).

You'll partner closely with your Customer Value Architect (CVA) to monitor data health and remediate issues, and you'll grow your consultative and technical skills as you take on more complex engagements. As you build fluency with Mixpanel's product and the broader data landscape, you'll also start applying AI tools — MCP servers, agent workflows — to your own implementation work, and look for opportunities to sharpen how the team delivers.

Responsibilities

• Own onboarding, implementation, and data health for a portfolio of primarily SMB and scaled accounts, using existing resources, frameworks, and playbooks to execute

• Field and resolve reactive technical support issues from customers — troubleshooting instrumentation, data discrepancies, and configuration questions — alongside proactive implementation work

• Monitor data health on assigned accounts and proactively work with your CVA on a remediation plan

• Partner with your CVA to define outcomes for customer projects and their associated business impact at the customer's organization

• Keep projects organized and on track, manage expectations and competing priorities, and escalate appropriately when you hit a wall

• Support pre-sales teams in aligning on business goals and metrics that guide data architecture and project outcomes, where these haven't already been uncovered during the sales process

• Engage with customers' engineering, product management, and marketing teams to build rapport and run technical meetings with clear agendas in pursuit of clear outcomes

• Explain technical concepts — data architecture, instrumentation, integration — to varied audiences, tying them back to the problems they're meant to solve

• Run Mixpanel implementations using standard methods, including SDKs, CDPs, event streaming, reverse ETL, and warehouse connectors

• Stay familiar with data governance best practices and lead data governance discussions with customers

• Use AI tools (MCP servers, agent workflows) in your own implementation work to improve output and customize it to the situation

• Identify gaps in implementation playbooks and best practices, and suggest improvements to managers and senior ICs

• Partner with your Account Executive, CVA, and Customer Engineer on business and technical handoffs

• Work with senior members of the team to experiment with new approaches to AI and process improvements

We're Looking For Someone Who Is:

• Has technical, client-facing experience — implementation, onboarding, professional services, technical consulting, solutions, or support engineering are all strong backgrounds, including candidates whose customer exposure has primarily been through support tickets or email

• Skilled at using existing resources, frameworks, and processes to execute — you don't need to build the playbook from scratch to deliver a great outcome with it

• Has led or project-managed technical, customer-facing work — pure technical troubleshooting experience alone isn't enough; we're looking for some track record of owning implementation/onboarding work or a project from start to finish

• Comfortable discussing data architecture, schemas, instrumentation, and API concepts, and conceptually fluent in tools like SQL / Python / SDKs / CDPs / data warehouses (Snowflake, BigQuery, Redshift, etc.) — deep hands-on coding expertise is not required; understanding how these pieces fit together and speaking to them confidently matters more

• Familiar with product analytics implementation methods like SDKs, Customer Data Platforms (CDPs), Event Streaming, Reverse ETL, etc.

• Demonstrates familiarity with nearly all aspects of the Mixpanel product

• Demonstrates familiarity with analytics best practices and common implementation patterns across business segments and verticals, and can map those onto customer projects

• Understands basic B2B SaaS post-sales delivery dynamics and uses that knowledge to help set scope and timelines and support basic discovery and project management

• Able to manage timelines, expectations, and competing priorities, and knows when to escalate

• Genuinely curious about and engaged with AI — has experimented with AI tools, workflows, scripts, or agents to solve a problem, and has a point of view on where AI is useful today

• Customer-facing and consultative skills can still

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