Principal Engineer, Data Services & Data Platform

What you'll do

• Define and drive the multi-year technical roadmap for enterprise data services.
• Design and build highly available, scalable, and resilient distributed data systems.
• Establish reusable architectural patterns for data ingestion, processing, storage, and delivery.
• Define standards for data products, schemas, lineage, and contracts to support AI/ML workloads.
• Translate business requirements from stakeholders into durable technical solutions.
• Resolve complex scaling challenges and mentor senior engineering staff to raise team standards.
• Ensure the delivery of trusted, discoverable, and high-quality data for analytics and observability.

What we're looking for

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• 15+ years of experience designing and delivering large-scale distributed systems or data platforms.
• Experience in data services, cloud platforms, distributed storage, data processing, and service-oriented architectures.
• Programming experience in one or more languages such as Java, Go, Python, or C++.
• Extensive experience building and scaling multi-tenant SaaS or enterprise data platforms from early-stage design to global production (preferred).
• Proficiency with a modern data stack, including Kubernetes, Kafka, Flink, Spark, object storage, lakehouse architectures, and distributed SQL engines (preferred).
• Proven ability to support modern AI/ML workloads, including experience with feature stores, vector/unstructured data, model evaluation, and generative AI systems (preferred).
• Deep understanding of the data lifecycle, including practical experience with governance, data quality, lineage, cataloging, security, privacy, and regulatory compliance (preferred).