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

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 — GCP BigQuery and dbt a plus

Proven experience architecting large-scale data warehouses or lakehouses

Solid understanding of data modeling concepts including dimensional modeling and streaming architectures; experience with vector stores is a plus

Strong understanding of data governance; experience implementing data catalogs a plus

Talent shows up in a lot of different ways, and we mean that. We welcome candidates from all backgrounds and experience levels, including military members and their spouses and those without a traditional degree or tech background. If this role speaks to you, apply.

Why You’ll Like Working on Team Applied The best work happens when smart people move fast, together. For over 40+ years, Applied has built technology that solves real problems for insurance professionals - and we’re still pushing what’s possible.

You’ll be part of our people-first culture built on trust, inclusion, and growth - where you’re supported to deliver, collaborate with teammates who care, and grow with leaders invested in your success.

We invest in the whole person, not just the role. Our benefits and resources are built to support your health, your time, and your life outside of work:

Medical, Dental, and Vision Coverage

Holiday and Vacation Time

Health & Wellness Days

A Bonus Day for Your Birthday

We leverage AI tools to streamline parts of our recruitment workflow (such as resume parsing and interview scheduling). However, final decisions are always conducted by real humans.

Applied Systems is proud to be an Equal Employment Opportunity Employer. Diversity and Inclusion is a business imperative and is a part of building our brand and reputation. At Applied, we don’t discriminate, and we are committed to recruit, develop, retain, and promote regardless of race, religion, color, national origin, sexual orientation, gender identity, disability, age, veteran status, and other protected status as required by applicable law.

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