Senior DataOps Engineer

This is a fully remote position, open to applicants in Colombia, +1 more country.

📋 Description

• Develop and sustain production-quality data pipelines that transfer data from business applications into Snowflake.

• Integrate data from HubSpot, NetSuite, partner systems, product usage sources, and various other SaaS applications.

• Design and manage raw, staging, intermediate, and governed data models.

• Create historical and point-in-time datasets that facilitate the analysis of customers, pipeline, ARR, renewals, and other crucial business metrics.

• Convert business concepts into reusable governed data models.

• Establish consistent definitions and relationships across CRM, ERP, product, and other source systems.

• Develop and maintain semantic and metrics layers for Finance, Revenue Operations, leadership, BI tools, and authorized AI applications.

• Collaborate with Finance and Revenue Operations to resolve data and metric discrepancies.

• Create reliable datasets, metrics, dashboards, and reporting models for executive and operational reporting.

• Facilitate self-service analytics and decrease reliance on ad-hoc SQL analysis.

• Configure and manage ETL/ELT tools such as Fivetran, Matia, or equivalent technologies.

• Develop custom data integrations utilizing APIs, SQL, and Python.

• Partner with source-system owners to comprehend schemas and enhance upstream data quality.

• Establish dependable processes for transferring governed data back into operational systems when suitable.

• Implement data-quality testing, monitoring, documentation, lineage, exception handling, and access controls.

• Organize governed business data to support AI-enabled analytics, natural-language querying, agentic workflows, and workflow automation.

• Work collaboratively 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 best practices in data architecture, governance, scalability, reliability, and maintainability.

⛳️ 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 extensive experience in designing and maintaining production data models.

• Practical experience with Snowflake or a similar cloud data warehouse.

• Proven experience in building production-quality ETL/ELT pipelines and integrating SaaS applications into a data warehouse.

• Familiarity with CRM data and systems such as HubSpot or Salesforce.

• Experience with ERP, billing, or financial data and systems.

• Knowledge in creating semantic layers, governed metrics, or reusable analytics models.

• Proficient in Python for data transformation, automation, and API integrations.

• Experience utilizing APIs to integrate data across various business systems.

• Familiarity with BI platforms and developing dashboards, reporting models, and analytics solutions for non-technical business users.

• Strong understanding of data quality, testing, monitoring, lineage, access control, documentation, and maintainability.

• Experience in designing historical and point-in-time data models.

• Ability to transform ambiguous business requirements and metric definitions into scalable technical solutions.

• Excellent analytical thinking and problem-solving abilities.

• Strong communication and collaboration skills, capable of working effectively with both technical and non-technical stakeholders.

• Experience in collaborative, cross-functional environments.

• Conversational proficiency in English.

• Familiarity with NetSuite.

• Experience with HubSpot.

• Knowledge of dbt or similar data transformation and modeling frameworks.

• Experience with Fivetran, Matia, or comparable ingestion and integration platforms.

• Familiarity 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.

• Background 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 accessible to AI or LLM applications.

• Familiarity with AI-enabled analytics, natural-language data querying, and agentic workflows.

🏝️ Benefits

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work options.

• Professional development opportunities and training programs.

• Generous vacation and paid time off policies.

• Collaborative and inclusive company culture.