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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data Architect - **Company:** Supplyhouse LLC - **Location:** Melville, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $144,433.0 - $180,541.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, BigQuery, Cloud Storage, Cluster Analysis, Cyber Security, Information Systems, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Systems, Data Vault Modeling, Data Warehousing, Distributed Computing Environment, Data Flow Control, Identity and Access Management, Metadata, Meta-Data Management, Operational Data Store, Performance Tuning, Query Optimization, Data Streaming, Management of Software Versions, Enterprise Data Management, Google Cloud, Data Layers, Integration Tests, Google Cloud Functions, Domain Driven Design, Stream Analytics - **Published:** August 28, 2026 - **Apply:** https://www.dice.com/job-detail/5b113f7c-f949-43ac-9286-db3e631732fc ## About the Role * Bachelor's degree in CS, Engineering, Information Systems, or a related field * A minimum of 10 years of experience in Data Engineering, Architecture, or Platform Engineering * A minimum of 5 years of experience designing enterprise-scale cloud data architectures (AWS, Azure, or Google Cloud Platform) * Expertise in data warehousing, Lakehouse architecture, distributed processing, streaming, and enterprise data modeling (Kimball, Inmon, Data Vault, and/or domain-driven design) * Strong understanding of data governance, metadata management, and security architecture * Experience leading cross-functional architecture initiatives * Proven ability to influence senior stakeholders and executives, * A minimum of 7 years of experience in Data Engineering, Analytics Engineering, or Data Platform roles with significant production ownership * Deep experience with Google Cloud Platform services relevant to data engineering (e.g., Cloud Storage, Pub/Sub, Dataflow, Cloud Composer, Cloud Functions/Run, Secret Manager, IAM) * Experience with BigQuery best practices (partitioning/clustering, incremental strategies, performance tuning, cost controls) * Strong understanding of BI consumption needs (star schema design, incremental refresh considerations, semantic consistency/metrics definitions) * Experience implementing data mesh or domain-oriented ownership models, AI/ML feature platform exposure, regulated environment experience, and strong cloud cost management acumen * Industry certifications (AWS Solutions Architect, Azure Architect, Google Cloud Platform Professional Architect) ## Description * Design, build, and maintain scalable ELT/ETL pipelines into BigQuery for core domains (orders, customers, products, inventory, fulfillment, procurement, marketing) * Build orchestration patterns with strong operational rigor (retries, idempotency, backfills, SLAs/SLOs, incident response) to enable reliable delivery * Implement data quality and testing frameworks (freshness checks, anomaly detection, unit/integration tests) and standardize monitoring/observability * Standardize CI/CD and infrastructure-as-code patterns for data systems and guide teams on best practices for ingestion, transformation, and orchestration * Lead modernization initiatives such as legacy warehouse to cloud lakehouse migrations and platform upgrades * Create and own curated, analytics-ready datasets and models (dimensional/conformed, semantic-ready layers) that make reporting fast, consistent, and self-serve * Establish and enforce standards for conceptual, logical, and physical data modeling * Oversee domain-driven modeling and data product design through reusable patterns and reference implementations * Establish data architecture standards including modeling conventions, schema evolution/versioning, incremental loading strategies, and warehouse performance patterns * Define and evolve the enterprise data architecture vision aligned to business strategy, including canonical data models, domain boundaries, and integration patterns * Lead architecture decisions for data warehousing, lakehouse, streaming, MDM, and operational data platforms * Evaluate and select strategic data technologies and vendors * Partner with Security and Legal to design privacy and compliance architectures (GDPR/CCPA/SOC2-aligned approaches) and establish enterprise governance frameworks * Build governance fundamentals including documentation, lineage/metadata, access controls, and PII handling * Act as the escalation point for data architecture decisions and mentor senior engineers/architects through reviews, templates, and best practices * Partner with application engineering and analytics stakeholders to define data contracts and ensure reliable upstream/downstream integrations * Translate business capabilities into scalable data platform solutions * Optimize cost and performance across BigQuery workloads (query optimization, partition pruning, clustering strategies, and workload management where applicable) * Drive adoption of emerging capabilities (real-time analytics, AI enablement, semantic layers, data mesh) and develop multi-year data roadmap and maturity models * Operate at enterprise scope across multiple business domains * Influence strategy beyond the immediate team and set technical direction that others follow, * Remote employees are expected to work in a distraction-free environment. Personal devices, background noise, and other distractions should be kept to a minimum to avoid disrupting virtual meetings or business operations. * Applicants must be currently authorized to work in the U.S. on a full-time basis. SupplyHouse.com will not sponsor applicants for work visas. * SupplyHouse.com is an Equal Opportunity Employer. We welcome and encourage individuals of all backgrounds, experiences, and perspectives to apply. Employment decisions are based on qualifications, merit, and business needs. * To ensure fairness and trust in our hiring process, we ask that all application materials, assessments, and interview responses reflect your own thinking and perspective. You may use AI tools to assist in preparing your responses, as long as this use is clearly disclosed and you can speak authentically to your ideas and work. Our focus is on honesty, judgment, and how you approach problem-solving. We appreciate your transparency and look forward to learning more about your skills. * We are committed to providing a safe and secure work environment and conduct thorough background checks on all potential employees in accordance with applicable laws and regulations. * All emails from the SupplyHouse team will only be sent from an @supplyhouse.com email address. Please exercise caution if you receive an email from an alternate domain. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [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) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Making Data Warehouses fast. 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