Location: Remote (US preferred)
Employment Type: Full-time
Travel: Occasional travel may be required
Work Authorization: Must be authorized to work in the US (no visa sponsorship available)
Our client is a VC-backed infrastructure software company enabling organizations to connect, secure, and observe modern applications — APIs, microservices, and data — through a leading API and Service Mesh Management platform.
Founded in 2017 and valued at $1B in 2021, the company serves large enterprises across industries and geographies, with deep expertise in cloud computing, Linux, containers, Kubernetes, service mesh, APIs, security, application modernization, GraphQL, and eBPF.
The OpportunityThe company is seeking a Revenue Operations Engineer to build, maintain, and evolve the technical foundation of its go-to-market systems. This role sits at the intersection of data engineering, analytics, systems administration, and applied software engineering, working across Sales, Marketing, Customer Success, Finance, Engineering, and Content to ensure revenue data is accurate, accessible, and actionable.
This is a high-impact, autonomous role where the engineer will navigate ambiguous problem spaces, propose solutions independently, and work across a diverse technical stack — from Salesforce to dbt models to terminals and APIs. This is not a narrowly scoped analyst role.
Key ResponsibilitiesData & Analytics EngineeringBuild, maintain, and optimize data pipelines supporting revenue, marketing, and customer analytics
Develop and maintain analytical models using dbt to ensure data is reliable, well-documented, and reusable
Own data transformations and modeling logic across core GTM datasets (leads, accounts, opportunities, product usage, revenue)
Partner with stakeholders to translate vague business questions into testable data models
Configure, monitor, and troubleshoot data syncs using tools such as Fivetran, BigQuery Data Transfer, or Airbyte
Ensure data integrity across Salesforce, Marketo, and downstream analytics platforms
Diagnose sync issues, schema changes, and upstream system quirks proactively
Gather requirements from multiple business units: Sales, Marketing, Customer Success, Finance, Engineering, Solutions Engineering, Content Marketing
Navigate incomplete or conflicting inputs and independently determine:
What the actual problem is
The simplest viable solution
A better long-term solution
Document decisions, assumptions, and tradeoffs for team alignment
Ideate, hypothesize, and test solutions independently
Leverage AI tools (OpenAI APIs, copilots, etc.) to accelerate experimentation and iteration
Challenge existing approaches and propose improvements
Manage multiple projects and shifting priorities in parallel
Work across Salesforce configuration, SQL/dbt modeling, terminal debugging, API testing, and light web tooling
Perform end-to-end testing across systems (e.g., form → Marketo → Salesforce → warehouse → dashboard)
1–4 years of experience in Revenue Operations, Analytics Engineering, Data Engineering, or Sales/Marketing Systems
Strong working knowledge of SQL and relational data modeling concepts
Hands-on experience with at least one modern analytics stack (e.g., BigQuery + dbt)
Comfort operating in ambiguous environments with minimal direction
Ability to explain technical concepts clearly to non-technical stakeholders
Confidence to challenge assumptions and propose better approaches
This role provides a unique opportunity to work across multiple GTM systems and have a direct impact on revenue operations and data-driven decision making. The engineer will work with modern analytics stacks, automation, and SaaS infrastructure tools while helping shape the company’s go-to-market technology foundation.
Equal OpportunityThe client is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability.
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