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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data Engineer - **Company:** AI Enabled Solutions LLC - **Location:** United States (Remote available) - **Salary:** $160,000.0 - $260,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Azure, Big Data, BigQuery, Cloud Computing, Code Review, Data Architecture, Information Engineering, Data Governance, Software Design Patterns, Dimensional Modeling, Python (Programming Language), Windows Servers, Online Analytical Processing, Online Transaction Processing, Windows PowerShell, Ansible, Runbook, Salesforce.Com, Software Engineering, Virtual Machines, Software Vulnerability Management, Cloud Platform System, Generative AI, Infrastructure Automation Frameworks, Information Technology, Data Lineage, Data Pipelines - **Published:** September 4, 2026 - **Apply:** https://www.builtincolorado.com/job/principal-data-engineer/11014427?handler=ApplyRedirect ## About the Role * 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. ## Description Define and govern enterprise-scale data architecture across batch, streaming, warehouse, lakehouse, transactional, and AI use cases. Establish standards for data quality, lineage, access, cataloging, governance, observability, and SLAs. Architect AI-enabled workflows, resolve complex architecture issues, influence roadmaps, and mentor engineers through hands-on technical leadership. The role requires 15+ years of software, data engineering, or architecture experience and expertise in large-scale data platforms and modeling. The summary above was generated by AI, Applied Systems is looking for a Principal Data Engineer 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, Our candidates' personal information and online safety are top of mind. Applied communicates with candidates only via a secure @appliedsystems.com email address or through our official careers portal. Recruiters will never request payments or ask for financial account or sensitive personal information like Social Security numbers. AI Utilization 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. EEO Statement 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. #LI-Hybrid / #LI-Remote #LI-US, Remote or Hybrid United States Mid level Mid level Artificial Intelligence * Cloud * Payments * Software * Business Intelligence * Generative AI * Automation Administer hybrid Windows Server infrastructure across colocation, on-premises, Azure, and GCP environments. Manage virtual machines, cloud resources, patching, upgrades, backups, monitoring, alerts, incident response, vulnerability remediation, and root cause analysis. Develop automation using PowerShell, Python, Ansible, and infrastructure-as-code tools for provisioning, remediation, and self-healing workflows. Maintain documentation and runbooks while collaborating with engineering, IT support, security, and operations teams. Top Skills: AnsibleAppdynamicsArm TemplatesBashDatadogEsxiGitlab Ci/CdGoogle Cloud Platform (Gcp)GrafanaAzureNew RelicOpentelemetryPatchmypcPowershellPythonSccmSignozSolarwindsTerraformVcenterVmware VsphereWindows ServerWsus Applied Systems Customer Success Manager 7 Days Ago Remote or Hybrid 65K-95K Annually Junior 65K-95K Annually Junior Artificial Intelligence * Cloud * Payments * Software * Business Intelligence * Generative AI * Automation Manage assigned customer accounts, driving satisfaction, product adoption, retention, account growth, and advocacy. Responsibilities include resolving customer issues, developing account and strategic success plans, leading quarterly business reviews, analyzing customer health and usage metrics, communicating product feedback, and collaborating with internal teams. The role requires strong communication, presentation, organization, empathy, and creative problem-solving skills, with travel up to 15%. Top Skills: Salesforce Applied Systems ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Technical Documentation - How Can I Write Them Better and Why Should I Care?](https://www.wearedevelopers.com/videos/681-technical-documentation-how-can-i-write-them-better-and-why-should-i-care) - [Dev & Test in the Cloud? 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