You will build and maintain production-grade data pipelines and models to integrate data from various SaaS platforms into Snowflake. Additionally, you will establish consistent business definitions and metrics to enable trusted reporting and self-service analytics for leadership and operational teams.
Gorilla Logic is looking for a Senior Analytics Engineer with strong experience building scalable, governed business data platforms. In this role, you will work at the intersection of Finance, Revenue Operations, and business systems to transform data from platforms such as HubSpot, NetSuite, partner systems, and product-usage sources into reliable and reusable business data products.
You will be responsible for building and maintaining data pipelines and models in Snowflake, establishing consistent business definitions across systems, and enabling trusted analytics and reporting for leadership and operating teams. This is a hands-on role for someone who enjoys translating complex business requirements into well-designed, production-ready data solutions.
Responsibilities
Build and maintain production-grade data pipelines from business applications into Snowflake.
Integrate data from HubSpot, NetSuite, partner systems, product-usage sources, and other SaaS applications.
Design and maintain raw, staging, intermediate, and governed data models.
Build historical and point-in-time datasets to support analysis of customers, pipeline, ARR, renewals, and other key business metrics.
Translate business concepts such as Customer, Contract, ARR, Pipeline, Renewal, Billing, Partner, Product Usage, and Customer Health into reusable governed data models.
Establish consistent definitions and relationships across CRM, ERP, product, and other source systems.
Build and maintain semantic and metrics layers that provide consistent business definitions across Finance,
Revenue Operations, leadership, BI tools, and approved AI applications.
Partner with Finance and Revenue Operations to reconcile data and metric differences across operational and financial systems.
Build trusted datasets, metrics, dashboards, and reporting models for executive and operational reporting.
Enable self-service analytics and reduce dependency on one-off SQL analysis.
Configure and manage ETL/ELT tooling such as Fivetran, Matia, or equivalent technologies.
Develop custom data integrations using APIs, SQL, and Python when packaged connectors are not sufficient.
Partner with source-system owners to understand schemas and improve upstream data quality.
Build reliable processes for moving governed data back into operational systems when appropriate.
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