Marketing Automation Engineer
Inactive
USA. at this time we can only support hiring in the following US states: CA, MD, MA, IL, OR, WA, CO, TX, FL, PA, LA, MO, or DCFull-TimeMiddle
This job is no longer active. We keep the page for reference, but the employer may not accept new applications.
Salary not disclosed
Job Details
- Required Skills
- SQLData engineeringRESTful APIsHubSpotBigQuery
Requirements
- Advanced Automation Skills: Deep proficiency in n8n (Node-based logic, HTTP requests, custom JS nodes) to handle complex orchestration
- Data Engineering Expertise: Strong technical command of BigQuery (SQL/DDL) and Segment (Protocols, Engage, Identity Resolution, Source/Destinations)
- CRM Mastery: Extensive experience with HubSpot, specifically regarding Custom Objects and API-driven workflows
- Action-Oriented Mindset: You value shipping functional automation over theoretical architecture and have a proven bias for action, learning from feedback and iterating improvements.
- AI Tool Mastery: Daily mastery of AI coding assistants like Cursor and Claude to accelerate delivery
- Stack Agnostic Approach: You aren't married to one tool; you possess the ability to plug into any API to get the job done
- Engineering Background: Experience as a data engineer with strong exposure to growth/marketing data sources. Alternatively a marketing operations professional with demonstrably strong AI automation ability
- B2B SaaS Experience: Familiarity with the unique data challenges and velocity of a high-growth B2B SaaS environment.
Responsibilities
- Architect Custom Integrations: Build bespoke workflows between a fragmented stack (Ads, Web, Social, Intent data) using n8n and BigQuery, bypassing the limitations of native connectors to create seamless data flow
- Orchestrate Data Pipelines: Improve the Segment / BigQuery / HubSpot pipeline. You will ensure high-fidelity event tracking and transform raw data signals into actionable marketing triggers
- Drive Rapid Prototyping: Transition from abstract marketing ideas to functional automated workflows in hours, not days. You will build, test, and iterate with a relentless bias for action
- Leverage AI-Native Development: Utilize tools like Cursor and Claude as your primary leverage to write custom scripts, handle API edge cases, and automate complex data cleaning tasks efficiently
- Optimize the Stack: Continuously identify bottlenecks in the GTM process and engineer technical solutions to either remove or optimise them