GTM Tools Data Infrastructure Engineer

Key Responsibilities

• Architect, develop and maintain scalable batch and streaming pipelines that ingest data from GTM systems (for example Salesforce, HubSpot, Marketo, Zendesk) into platforms such as Snowflake, Redshift or BigQuery.
• Own RevOps data tables: create schema, write performant SQL, monitor usage and tune queries for speed and cost efficiency.
• Build and manage REST and GraphQL API integrations to bring in third-party or internal data sources that enrich revenue analytics.
• Develop and schedule automation scripts to validate, transform and load data while applying data quality rules.
• Partner with Revenue Operations, Finance and Product Analytics teams to understand reporting needs and translate them into robust datasets and dataflows.
• Maintain documentation for data models, pipelines and integration points; promote data literacy across GTM stakeholders.
• Troubleshoot pipeline failures and data discrepancies, coordinating with DevOps or external vendors when deeper infrastructure issues arise.
• Continuously evaluate manual data collection processes and propose automation or tooling improvements to increase accuracy and reduce effort.

Qualifications

• 5+ years in data engineering or analytics engineering, ideally supporting GTM or Revenue Operations functions.
• Advanced SQL proficiency, including query optimization and performance tuning in large-scale data warehouses.
• Hands-on experience building ETL/ELT workflows with tools like Alteryx, Fivetran, dbt, Airflow or similar orchestration frameworks.
• Proven track record of developing API integrations (REST, SOAP, GraphQL) and handling authentication, rate limiting and error recovery.
• Familiarity with BI and visualization platforms such as Power BI, Tableau or Looker; ability to structure tables for self-service analytics.
• Strong understanding of data modeling concepts (star/snowflake schemas, slowly changing dimensions, CDC).
• Excellent problem-solving ability and attention to detail when dealing with complex data sets and ambiguous requirements.
• Clear communication skills for explaining technical topics to non-technical stakeholders.
• Ability to manage multiple priorities, deliver to deadlines and thrive in a fast-paced, data-driven culture.
• Prior exposure to revenue operations metrics (pipeline, bookings, ARR, churn) and SaaS business models

More Information

• Remote work setup
• Equipment provided
• HMO, 13th month pay
• Work Schedule: Monday to Friday, US business hours