Principal Data Architect

Job Description
Applied Systems is looking for a Principal Data Architect to shape the architectural
foundation of our Data and Analytics capabilities as we scale to enable better insights and
lay the groundwork for AI across the enterprise. The ideal candidate brings deep data
architecture expertise with a commitment to embracing AI and enabling the success of
engineering teams across Applied.
At Applied, Principal architects are force-multipliers - technical leaders and practitioners
who are passionate about designing, guiding, and teaching by doing. You will live our
Leadership Principles: owning outcomes, insisting on the highest standards, and inventing
and simplifying solutions for our customers and teams.
You will have an AI-First approach to architecture with a view of AI and automation as
leverage to scale your impact beyond individual throughput. You will define the long-term
vision for AI-enabled data architecture, design and govern agentic workflows
with appropriate guardrails, and surface system-level insights that raise quality and
velocity across the domain.
What You'll Do
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

What You'll need to succeed
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