Own the definition, structure, and reliability of data originating from revenue platforms (e.g., Salesforce, GTM tools, automation systems)
Serve as the primary decision owner for GTM-sourced tables and views used for revenue execution, forecasting inputs, lifecycle tracking, and signal-based workflows
Design and evolve core GTM data models across Salesforce, ETL, and analytics layers
Partner with Data Engineering to align GTM schemas with enterprise data models and define clear data contracts between source systems and downstream consumers
Partner with Data Science / Analytics to ensure revenue data is interpretable, statistically sound, and reflects how the business actually operates
Own clarity around data ownership boundaries, shared dependencies, and escalation paths when upstream or downstream changes impact revenue integrity
Define and uphold data quality, freshness, consistency, and documentation standards for revenue platforms
Monitor and improve pipeline reliability, performance, and scalability, proactively identifying fragile or redundant transformations
Identify opportunities to automate manual or error-prone data workflows and reduce operational overhead
Act as a data thought partner to Platforms & Infrastructure, Revenue Operations, Analytics, and Security — advising on feasibility, tradeoffs, and sequencing for data-heavy initiatives

Requirements

7+ years of experience in data engineering or data systems roles within SaaS or technology companies
Deep experience designing and operating production data pipelines
Proficient in SQL and experienced in data modeling
Hands-on experience with modern data stacks (e.g., Snowflake, BigQuery, Redshift)
Experience with ETL / ELT tooling (e.g., dbt, Airflow, Census, or similar)
Understand Salesforce data models and common GTM system architectures
Ability to translate business concepts into durable, well-structured data models
Clear communication with both technical and non-technical partners.
Preferred: Experience supporting revenue, sales, or customer lifecycle data
Familiarity with event-based data platforms (e.g., Data Cloud or equivalents)
Experience working alongside platform engineering and security teams
Exposure to data governance, access controls, and compliance considerations
Experience mentoring or guiding other data practitioners

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringdata systemsproduction data pipelinesSQLdata modelingETLELTdata governancedata qualitydata automation

Soft Skills

clear communicationcollaborationproblem-solvingmentoringdata thought partnership