Principal Data Engineer

Applied Systems is seeking a Principal Data Engineer to shape the architectural foundation of its data and analytics capabilities and support enterprise AI initiatives. The role defines and governs data architecture, establishes engineering standards, and guides teams through technical leadership and mentorship.

Responsibilities:

• 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

Requirements:

• deep data architecture expertise
• 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
• Adaptability, resilience, and the ability to thrive in ambiguity with iteration
• Excellent communication skills, able to meet your audience where they are and explain complex problems clearly
• Expertise across data and software technologies
• Proven experience architecting large-scale data warehouses or lakehouses
• Solid understanding of data modeling concepts including dimensional modeling and streaming architectures
• Strong understanding of data governance
• GCP BigQuery and dbt a plus
• experience with vector stores is a plus
• experience implementing data catalogs a plus