Senior Data Engineer

Kong Inc. is a leading developer of API and AI connectivity technologies, and they are seeking a Senior Data & AI Engineer to join their 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, focusing on building and maintaining reliable data pipelines and scalable models while integrating AI tools securely and cost-effectively.

Responsibilities:

• 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
• 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
• 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
• 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
• 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
• 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
• 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

Requirements:

• 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-augmented generation (RAG), and/or fine-tuning
• Strong SQL and Python skills
• A security-first mindset with experience managing data access controls in cloud data platforms
• Strong communication skills and the ability to collaborate across technical and non-technical teams
• Experience with Anthropic's Claude API or Claude for Enterprise
• Familiarity with vector databases (e.g., Pinecone, Weaviate, or Snowflake's native vector support)
• Experience with dbt for data transformation
• Experience with a workflow orchestration tool such as Airflow or Prefect
• Familiarity with data observability tools (e.g., Monte Carlo, Metaplane)
• Background supporting Sales, Finance, or Revenue Operations use cases
• Experience building internal AI tools or copilots for business teams