RevOps Engineer

Sorry, this job was removed at 04:56 a.m. (UTC) on Wednesday, Sep 16, 2026
Be an Early Applicant
Hiring Remotely in United States
Remote
130K-170K Annually
Mid level
Artificial Intelligence • HR Tech • Professional Services
The Role
Build and maintain revenue operations data pipelines, dbt models, integrations, and GTM systems across Salesforce, Marketo, warehouses, and analytics platforms. Diagnose synchronization and schema issues, ensure data integrity, translate ambiguous business needs into data solutions, test end-to-end workflows, and collaborate with Sales, Marketing, Customer Success, Finance, and Engineering. The role also involves experimentation with AI tools, technical documentation, and managing multiple projects independently.
Summary Generated by Built In
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 ResponsibilitiesData & 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.

Skills Required

  • 1-4 years of experience in Revenue Operations, Analytics Engineering, Data Engineering, or Sales and Marketing Systems
  • Strong working knowledge of SQL
  • Knowledge of relational data modeling concepts
  • Hands-on experience with at least one modern analytics stack, such as BigQuery and dbt
  • Ability to operate in ambiguous environments with minimal direction
  • Ability to explain technical concepts clearly to non-technical stakeholders
  • Confidence challenging assumptions and proposing better approaches
  • Authorization to work in the United States without visa sponsorship

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Year Founded: 2014

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SourceDirect Talent is a talent advisory and recruiting firm serving seed and early-stage startups. It provides AI-powered recruiting solutions to help customers build go-to-market and engineering teams, alongside global people consulting. Its services cover end-to-end recruitment, immigration, HR, and advisory support, using AI talent agents, sourcing frameworks, and data-driven processes to help growing companies scale hiring and improve recruitment capacity.

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