Principal Data Engineer

Define large-scale data architecture decisions — batch/streaming platforms, warehouses, and lakehouses — and evaluate tradeoffs for quality, scalability, and long-term sustainability

Architect observability, alerting, and incident-response frameworks to monitor the health and SLAs of data pipelines across the organization; serve as the technical escalation point for complex data architecture problems

Partner across Applied teams to define standards for data quality, lineage tracking, access control, cataloging, and governance; establish SLAs/SLOs for critical data assets

Design data modeling standards across OLAP/warehouse (dimensional modeling), OLTP/transactional, streaming/real-time, and AI/vector/feature-store use cases

Define patterns for embedding AI and agent-supported workflows across the data engineering lifecycle, and enable teams to adopt them at scale

Define and enforce data engineering standards, best practices, and design patterns across the organization

Mentor and grow engineers through code reviews, design discussions, and technical guidance

Influence cross-functional roadmaps by translating business requirements into sound data architecture strategies

15+ years in software/data engineering or architecture with outstanding impact

Degree in Computer Science, a related field, or equivalent combination of education and experience

Expert knowledge of data architecture principles and best practices

Hands-on builder experience (actively coding, testing, and validating architecture at scale)

Proven ability to influence without authority

Pragmatic approach and obsessed with eliminating waste

Player-coach mindset with a commitment to teaching through action