Rather than primarily producing reports, this role owns how GTM data is ingested, transformed, modeled, and served. From the architecture level, you will define the data models, pipelines, and governance that power executive reporting and self‑service analytics. You will lead a small team of data analysts and work together with cross-functional data engineering resources, to operate hands‑on in architecture and implementation.

This role sits at the intersection of Data Engineering, Data Analytics, and RevOps, with a strong emphasis on building durable systems over one‑off reporting. The right candidate is a player/coach with the ability to design required changes and coach/train others to implement them.

• Design and own the end‑to‑end GTM data architecture, from source systems through transformation layers to BI consumption

• Build and maintain scalable data models that support full‑funnel and revenue analytics

• Develop and manage ELT/ETL pipelines integrating CRM, Marketing Automation, Finance, and Customer platforms

• Ensure data pipelines are reliable, monitored, performant, and well‑documented

• Partner with central data and engineering teams where applicable to align with broader architecture standards

Revenue & GTM Data Modeling

• Own the canonical data models for Marketing, Sales, Pipeline, Revenue, Retention, and Expansion

• Translate business processes into durable analytical schemas rather than report‑specific logic

• Standardize event, object, and metric definitions across systems

• Support complex revenue use cases such as lead attribution, forecasting, cohort analysis, funnel conversion, and lifecycle reporting

• Ensure data models support both historical accuracy and forward‑looking analysis

BI Enablement & Semantic Layer

• Define how transformed data is exposed to BI tools such as Power BI and Tableau

• Provide technical guidance on what is feasible, scalable, and sustainable

• 7–10+ years experience in data engineering, analytics engineering, or advanced BI roles

• Proven experience designing and maintaining analytical data architectures, including data cube/data warehousing setup

• Experience owning SQL‑based transformation layers and data models at scale

• Experience integrating multiple SaaS systems & tools into a unified analytical environment

• Experience working with GTM, revenue, or commercial data in a SaaS business with appropriate commercial acumen, capable of understanding the key drivers & priorities of different GTM teams inlcuding Marketing, Sales, Customer Success, Renewals, etc.

• Experience leading & coaching technical analytics or data teams for both career development and big-picture understanding

Required Skills

• Advanced SQL and data modeling expertise

• Strong understanding of ELT/ETL concepts and pipeline reliability

• Experience working with modern analytics stacks and cloud data platforms

• Strong understanding of revenue and GTM data structures

• Ability to balance business requirements with long‑term architectural integrity

• Clear, pragmatic communication with technical and non‑technical stakeholders

Preferred Qualifications

• Background in Analytics Engineering (dbt‑style modeling approaches)

• Experience supporting revenue forecasting or financial reporting models

• Experience operating in multi‑region SaaS environments