Principal Data Engineer

Join an AI-first global organization as a Principal Data Engineer. In this role, you will architect highly scalable, secure, and reliable enterprise data platforms using Agile methodologies. You will provide deep expertise in cloud data infrastructure and pipeline architecture, making critical architectural decisions and facilitating collaboration across various domains. You will also implement automated data pipeline monitoring and partner with Analytics Engineering to ensure optimal performance of production-ready repositories.

- Architect highly scalable, secure, and reliable enterprise data platforms using Agile methodologies. - Drive substantial impact on the division’s reputation and technical effectiveness by independently assessing complex scenarios. - Serve as the principal technical authority for the data engineering work group, establishing development standards and ensuring high pipeline availability.

- Advanced proficiency in SQL and software engineering programming languages, specifically Python, for pipeline automation, data scripting, and AI agent orchestration frameworks - Proven experience independently architecting real-time streaming topologies, high-volume event data ingestions, and custom API-driven connector/adapter frameworks - 10+ years of experience in data engineering, cloud data architecture, or specialized infrastructure roles, with a proven track record of delivering technical leadership for engineering work groups - Extensive experience designing, provisioning, and tuning production-grade cloud environments using Terraform to manage complex warehouse and networking configurations - Experience delivering data infrastructure iteratively within a fast-paced environment utilizing Agile management tools like Jira - Strong hands-on expertise architecting, optimizing, and managing multi-cluster enterprise data warehouses specifically within Snowflake - Background managing cross-functional technical data requirements and standardizing architectures across GTM, Finance, Product, CX, Legal, and People divisions - Deep experience designing and scaling advanced data platform solutions optimized for machine learning training pipelines, Vector DBs, and operational AI consumption - Experience creating organizational methods, techniques, and governance frameworks to automate data cleansing, quality monitoring, and system resilience at scale - Experience deploying and managing multi-region cloud data infrastructure architectures within AWS enterprise environments