We’re looking for a Staff Data Engineer to join a multi-disciplinary engineering team building modern, enterprise-grade data platforms.
In this role, you will design scalable data lakes, warehouses, and pipelines, define governance and quality standards, and drive data platform modernization across real, in-flight work where performance, reliability, and security are critical.
You’ll mentor more junior engineers, partner with leadership on data strategy, and bring an AI-forward mindset.
Define data architecture and platform strategy, leading design across pipelines, warehouses, and data lakes.
Build and optimize scalable data pipelines supporting batch and real-time processing.
Define and enforce data governance, quality standards, and compliance frameworks across the platform.
Build monitoring, logging, and alerting for data pipelines and services, and contribute to CI/CD workflows for data deployment and automation.
Drive data platform modernization, optimizing for performance, cost, and scalability.
Design and implement data contracts and event flows in collaboration with backend, platform, and engineering teams.
Lead the design and implementation of data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows.
Integrate data services with APIs, middleware, and third-party systems to support end-to-end data consumption.

7+ years of professional data engineering experience, with experience leading complex data platform initiatives
Strong system architecture background with expertise in distributed data systems
Expert proficiency in Python, Scala, and SQL
Deep expertise with cloud-native data platforms and enterprise data warehousing
Strong expertise in data pipeline orchestration and processing
Strong experience with streaming platforms and real-time data processing (e.g., Kafka, Kinesis, Pub/Sub)
Strong data modeling expertise and experience with data transformation
Strong experience with data quality, governance, and compliance frameworks
Strong experience with container orchestration and CI/CD for data systems
Strong experience building data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows
Demonstrated leadership and technical mentoring experience across a team or organization
Strong stakeholder communication skills, with the ability to translate technical depth across audiences
Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude and Cursor
Excellent problem-solving skills and the ability to navigate highly ambiguous technical and business challenges with sound judgment
Experience with data mesh or data fabric concepts, lakehouse architectures, or governance framework implementation is a plus.

Data Engineer

Key skills