RD Station
RD Station
RD Station — маркетинг, сату және клиенттерге қызмет көрсету командаларына арналған өзара байланысты құралдар әзірлейтін бразилиялық SaaS компаниясы. Оның платформасы лидтерді біліктендіру, электрондық пошта және WhatsApp науқандары, лендинг беттері, сату процестерін автоматтандыру, чат-боттар, омниканалды сөйлесулер, аналитика және жасанды интеллектке негізделген функцияларды қоса алғанда, маркетингті автоматтандыру, CRM және клиенттерге қызмет көрсету мүмкіндіктерін біріктіреді. Қолданбалар маркетплейсі мен әзірлеушілерге арналған API интерфейстері клиенттермен өзара әрекеттесу процестерін үйлестіріп, клиенттерді ұстап қалуды жақсартқысы және өсімді бірыңғай платформа арқылы басқарғысы келетін бизнес пен агенттіктер үшін интеграцияларды қолдайды.

Senior RevOps Data and AI Engineer

Build data pipelines, integrations, and LLM-powered automations for RD Station’s Customer Success operations. Deliver reliable, scalable solutions supporting RevOps, business intelligence, and Support.

Сипаттама

  • Act as the technology, data, and AI expert for the RevOps Retention squad within Data Solutions and GTM.
  • Build and manage production ELT/ETL pipelines and data models with BigQuery, Google Cloud, Airflow, and dbt.
  • Maintain data quality, governance, and documentation for Gainsight, BI, Customer Success, and Support systems.
  • Develop the data foundation for leadership dashboards in collaboration with BI and Business Analysts.
  • Create operational AI solutions, including LLM automations, agents, copilots, and AI-supported analysis.
  • Implement version control, deployment, observability, security, and cost controls for sustainable automations and AI products.
  • Automate cross-system workflows and integrations using APIs, webhooks, and integration platforms.
  • Enable system migrations and product launches through accurate data mapping and validation.
  • Turn Customer Success and Support requirements into prioritized technical solutions, coordinating with leadership and reporting progress.
  • Promote knowledge sharing through documentation, engineering practices, and responsible AI use.

Талаптар

  • Bring extensive experience as a Data Engineer or Analytics Engineer and the ability to work independently.
  • Have hands-on experience building and operating production data pipelines.
  • Demonstrate practical knowledge of BigQuery and Google Cloud.
  • Use Airflow and/or dbt for data orchestration and transformation.
  • Have applied LLMs or generative AI to automations or products through APIs and prompt development, even at an early stage.
  • Use Git and established engineering practices, including version control, documentation, and testing.
  • Read and write technical English for documentation and collaboration.
  • Hold a bachelor’s degree in Technology, Engineering, Computer Science, Statistics, or a related field, or have equivalent experience.
  • Take end-to-end ownership, act with initiative, and seek to understand Customer Success and Support workflows.
  • Communicate clearly with technical and non-technical audiences and consistently document new knowledge.

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