Senior DataOps Engineer - GP, Remote: Colombia - Costa Rica, Fulltime.

- This position is open to candidates located in Colombia or Costa Rica only - 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. Implement data-quality testing, monitoring, documentation, lineage, exception handling, and access controls. Structure governed business data to safely support AI-enabled analytics, natural-language querying, agentic workflows, and workflow automation. Collaborate with Finance, Revenue Operations, Engineering, Product, Customer Success, and external implementation partners. Troubleshoot data pipelines and integrations, validate outputs with business stakeholders, and document implemented solutions. Contribute to data architecture, governance, scalability, reliability, and maintainability best practices. Technical Requirements 5+ years of professional experience in Analytics Engineering, Data Engineering, Business Intelligence Engineering, or a similar hands-on data role. Advanced SQL skills with significant experience designing and maintaining production data models. Hands-on experience with Snowflake or a comparable cloud data warehouse. Experience building production-grade ETL/ELT pipelines and integrating SaaS applications into a data warehouse. Experience working with CRM data and systems such as HubSpot or Salesforce. Experience working with ERP, billing, or financial data and systems. Experience building semantic layers, governed metrics, or reusable analytics models. Working proficiency with Python for data transformation, automation, and API integrations. Experience using APIs to integrate data across business systems. Experience with BI platforms and developing dashboards, reporting models, and analytics solutions for nontechnical business users. Strong understanding of data quality, testing, monitoring, lineage, access control, documentation, and maintainability. Experience designing historical and point-in-time data models. Ability to translate ambiguous business requirements and metric definitions into scalable technical solutions. Strong analytical thinking and problem-solving skills. Strong communication and collaboration skills with the ability to work effectively with technical and nontechnical stakeholders. Experience working in collaborative, cross-functional environments. Conversational English level. Bonus Skills Experience with NetSuite. Experience with HubSpot. Experience with dbt or comparable data transformation and modeling frameworks. Experience with Fivetran, Matia, or similar ingestion and integration platforms. Experience with Pliable or another semantic or metrics-layer technology. Experience modeling SaaS business metrics such as ARR, bookings, pipeline, renewals, churn, retention, and customer health. Experience integrating product-usage data with CRM and financial data. Experience working in a B2B SaaS or private-equity-backed software environment. Experience building reverse ETL or other processes for synchronizing governed warehouse data back into operational systems. Experience making governed enterprise data available to AI or LLM applications. Familiarity with AI-enabled analytics, natural-language data querying, and agentic workflows.