Senior RevOps Data & AI Engineer

RD Station

. Serve as the technology, data, and AI subject-matter expert for the Retention squad within RevOps (Data Solutions / GTM).

Posted 10/8/2026full-timeRemote • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining ELT/ETL pipelines and data models within the Google ecosystem, with a strong focus on AI solutions and data governance. Proficient in translating customer needs into technical solutions while ensuring clear communication and documentation.

Highest-signal resume keywords

Data EngineeringBigQueryGoogle CloudAirflowLLM Automation

ATS Keywords

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Hard Skills

Data Pipeline DevelopmentData ModelingETL/ELT ProcessesData OrchestrationData TransformationVersion ControlTestingDocumentationAPIsGenerative AI

Soft Skills

Clear CommunicationHigh-Agency ProfileEnd-to-End Ownership

Tools & Technologies

GainsightBusiness Intelligence (BI)DbtAirflowGoogle Cloud

Industry Keywords

Data GovernanceCustomer SuccessData SolutionsRevOpsTechnical English Proficiency

Tech Stack

Tools & technologies

AirflowBigQueryCloudETL

About the role

Key responsibilities & impact

Serve as the technology, data, and AI subject-matter expert for the Retention squad within RevOps (Data Solutions / GTM).
Design, build, and maintain ELT/ETL pipelines and data models within the Google ecosystem, using BigQuery, Google Cloud, Airflow, and dbt.
Ensure the quality, governance, and documentation of data used by Gainsight, BI, and Customer Success and Support systems.
Prepare the data layer for leadership BI dashboards in partnership with BI and Business Analysts.
Design and implement AI solutions for operations, including LLM automations, agents, copilots, and AI-assisted analysis.
Establish version control, deployment, observability, security, and cost management for sustainable automations and AI products.
Automate processes and integrations between systems through APIs, webhooks, and integration platforms.
Support system migrations and new product launches through data mapping and validation.
Translate Customer Success and Support needs into technical solutions, prioritizing them with leadership and communicating progress.
Share knowledge through documentation, best practices, and the responsible use of AI.

Requirements

What you’ll need

Extensive experience as a Data Engineer or Analytics Engineer, with demonstrated autonomy.
Hands-on experience building and maintaining data pipelines in production.
Practical knowledge of BigQuery and Google Cloud.
Experience with data orchestration and transformation using Airflow and/or dbt.
Practical experience using LLMs / generative AI in automations or products (APIs, prompts), even if you are still early in this journey.
Git and sound engineering practices, including version control, documentation, and testing.
Technical English proficiency for reading and documentation.
Bachelor’s degree in Technology, Engineering, Computer Science, Statistics, or a related field, or equivalent experience.
High-agency profile, end-to-end ownership, and an interest in understanding Customer Success and Support workflows.
Clear communication with technical and non-technical audiences, along with a habit of documenting what you learn.