Senior Data Engineer

Are you ready to power the World's connections? If you don’t think you meet all of the criteria below but are still interested in the job, please apply. Nobody checks every box - we’re looking for candidates that are particularly strong in a few areas, and have some interest and capabilities in others. About the Role: We're looking for a Senior Data & AI Engineer to join our Revenue Analytics team. In this role, you'll own both the data infrastructure and AI systems that power revenue insights and intelligent experiences across the business. You'll be responsible for building and maintaining reliable pipelines and scalable data models and determining how we connect those data assets to AI tools — which solutions we invest in, and how we do it securely and cost-effectively. You'll sit at the intersection of data engineering, AI/ML, and platform architecture, with high visibility and real impact on our long-term data and AI strategy. What You'll Do: DATA INFRASTRUCTURE & PIPELINES - Design, build, and maintain ETL/ELT pipelines using Fivetran + Snowflake integrations to ingest data from a variety of sources into our Snowflake data warehouse - Develop and manage robust data models in Snowflake, ensuring data is structured for performance, reliability, and ease of use by analysts and business stakeholders - Use Hightouch to operationalize data by syncing warehouse data to downstream CRM, marketing, and sales tools - Monitor pipeline health, troubleshoot data quality issues, and implement alerting to proactively catch failures - Document data models, pipelines, and lineage to support a culture of data literacy and self-service analytics AI INFRASTRUCTURE & INTEGRATIONS - Integrate Claude and other LLMs directly with our Snowflake data warehouse, enabling AI-powered querying, summarization, and insight generation on top of live revenue data - Build and maintain data sources, semantic layers, and search services within Snowflake Cortex and connected AI platforms - Design and deploy AI agents that can reason over structured and unstructured revenue data to support go-to-market workflows AGENT ORCHESTRATION - Architect and manage multi-step agent workflows, coordinating across tools, APIs, and data sources to automate complex analytical and operational tasks - Evaluate and implement orchestration frameworks (e.g., LangChain, LlamaIndex, or custom solutions) best suited to our use cases AI STRATEGY & EVALUATION - Run rigorous evaluations of AI tools, models, and platforms to determine the best solution for each use case (e.g., Snowflake Cortex vs. Claude vs. Gemini vs. custom fine-tuned models) - Develop evaluation frameworks covering quality, latency, cost, and security to inform build vs. buy decisions and guide our overall AI roadmap - Stay current on the rapidly evolving AI landscape and proactively recommend new tools or approaches as the space matures SECURITY & GOVERNANCE - Implement and manage row-level security (RLS) in Snowflake to ensure AI tools only surface data that users are authorized to see - Maintain and evolve role-based access controls (RBAC) alongside new RLS policies - Contribute to data governance practices, including access controls, PII handling, and schema management - Partner with Data, Security, and Legal teams to establish AI data governance standards and guardrails COST MANAGEMENT & OPTIMIZATION - Monitor and manage AI credit consumption across Snowflake Cortex, API usage, and other platforms to keep spending within budget - Identify and implement optimizations — such as caching, prompt tuning, model selection, and query efficiency improvements — to reduce cost without sacrificing quality - Build reporting to give stakeholders visibility into AI spend and usage trends CROSS-FUNCTIONAL PARTNERSHIP - Partner with Revenue Operations, Finance, and Sales to understand data needs and translate them into scalable engineering solutions - Collaborate across technical and non-technical teams to deliver data and AI solutions that directly influence revenue strategy What We're Looking For: - 3+ years of experience in a data engineering, analytics engineering, or AI/ML engineering role - Hands-on experience with Snowflake, including data modeling, query optimization, Cortex Analyst, Cortex Search, semantic layers, and security model (RBAC, RLS) - Proficiency with Fivetran for pipeline orchestration and connector management - Experience with Hightouch or similar reverse ETL tools for syncing data to operational systems - Experience integrating LLMs (Claude, GPT-4, or similar) into production data workflows via API - Familiarity with agent orchestration frameworks and patterns (e.g., LangChain, LlamaIndex, CrewAI, or custom implementations) - Strong understanding of AI/LLM evaluation methodologies — you know how to measure whether an AI solution is actually working - Experience with prompt engineering, retrieval