Data Engineer

Data Engineer Data Platform & Engineering Build and maintain reliable data pipelines using tools such as Airbyte, Snowflake, and dbt. Design and optimize scalable data models that support analytics, reporting, search, and AI-powered applications. Develop and maintain dbt models, testing frameworks, documentation, and deployment processes. Ensure data quality, reliability, governance, and operational excellence across the data platform. Take direction from Senior staff to learn and support standard work and best practices. AI Application Development Build and enhance AI-powered applications that securely retrieve, interpret, and summarize business information. Design retrieval, context-management, prompt-engineering, and tool-calling approaches that improve accuracy, transparency, and user trust. Develop agent-based workflows that can complete multi-step business processes using approved tools and systems. Create APIs, services, and integrations that connect AI applications with internal platforms and business systems. Gain an understanding of business use of the AI agents and provide feedback for ensuring valuable results to users. Operations & Collaboration Monitor system health, application performance, data quality, AI usage, and operational costs. Troubleshoot issues across data pipelines, warehouse transformations, software services, and AI workflows. Apply security, access control, testing, logging, and governance best practices throughout the development lifecycle. Partner with business stakeholders to translate requirements into scalable and maintainable solutions. Leverage AI-assisted development tools to improve productivity while maintaining high standards for code quality, testing, and documentation. What You Bring? Required Qualifications Experience in software engineering, data engineering, analytics engineering, or a related technical discipline. Strong SQL skills and proficiency in at least one programming language, preferably Python. Experience building and supporting cloud-based data warehouses and production data pipelines. Hands-on experience with Snowflake and dbt. Experience with data integration or ingestion tools such as Airbyte. Experience developing applications that use large language models (LLMs), retrieval-augmented generation (RAG), tool calling, or agent-based workflows. Familiarity with AI-assisted software development tools such as Claude Code, GitHub Copilot, Cursor, Codex, or similar platforms. Understanding of APIs, source control, automated testing, CI/CD, and modern software engineering practices. Strong problem-solving skills with the ability to troubleshoot across interconnected systems. Effective communication skills and the ability to collaborate with both technical and business stakeholders. Preferred Qualifications Experience with Snowflake Cortex or other enterprise AI/LLM platforms. Experience designing semantic layers, metadata systems, or governed retrieval architectures. Familiarity with LLM evaluation frameworks, observability tools, token-cost optimization, and response quality monitoring. Experience implementing role-based access controls, data governance standards, and data privacy protections. Experience supporting internal applications from early-stage prototypes through enterprise-scale production adoption. #LI-NL1 #LI-Remote