RevOps Engineer

Revenue Operations Engineer 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) About Our Client 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 Opportunity The 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 Responsibilities Data & Analytics Engineering Build, 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 Systems & Integrations 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 Cross-Functional Problem Solving 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 Experimentation & Solution Design Ideate, hypothesize, and test solutions independently Leverage AI tools (OpenAI APIs, copilots, etc.) to accelerate experimentation and iteration Challenge existing approaches and propose improvements End-to-End Ownership 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) Ideal Candidate Profile 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 Why This Opportunity Stands Out 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 Opportunity The 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.