Data Pipeline Design
The ability to architect and build reliable data movement and transformation workflows that extract data from source systems, load it into a warehouse, and transform it into analytics-ready models.
Day-to-day use
Designing Fivetran connector configurations, writing dbt models to clean and standardise CRM exports, monitoring pipeline run schedules, debugging data freshness issues, and documenting lineage for downstream metrics.
Typical tasks
- ·Designing an ELT pipeline from Salesforce and Stripe into Snowflake
- ·building dbt staging models for opportunity data
- ·setting up data freshness alerts in Monte Carlo
- ·documenting table ownership and refresh cadences
Business outcome
Reliable data pipelines ensure all revenue dashboards reflect accurate, timely data — enabling confident forecasting, attribution, and performance management decisions.
Where this skill is applied
Technical Disciplines
RevOps AI Engineer
Builds AI-powered tools and workflows that automate revenue tasks, surface insights, and reduce manual work across the sales, marketing, and CS stack.
Integration Engineer
Builds and maintains the connections between CRMs, ERPs, marketing platforms, and third-party tools so data flows cleanly across the revenue stack.
Analytical Engineering
Transforms raw revenue data into clean, trusted models that power reporting, forecasting, and decision-making across the GTM organisation.
Data Governance Engineering
Establishes and enforces the data standards, hygiene rules, and stewardship processes that keep revenue data trustworthy — from duplicate management and field standardisation to master data management across the tech stack.
ML Engineer
Builds machine learning models that power revenue predictions — from churn scoring and lead ranking to pipeline forecasting and pricing optimisation.
Platform Engineer
Builds and maintains the core RevOps platform — the foundational layer of tools, APIs, and infrastructure that every other function depends on.
RevOps Data Engineer
Designs and maintains the data infrastructure — pipelines, warehouses, and integrations — that ensures revenue data is accurate, available, and actionable.
RevOps Systems Architect
Designs the overall revenue technology stack — selecting, connecting, and governing the systems that support the entire customer lifecycle.