This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Data Architect based in the United States.
This is a senior, hands-on architecture role focused on defining and shaping enterprise-wide data strategy across modern cloud platforms. The position plays a pivotal part in building scalable, secure, and high-performance data ecosystems that power analytics, reporting, and AI/ML initiatives. You will act as a key technical authority, setting architectural standards and guiding complex data design decisions across multiple domains. The role sits at the intersection of engineering, analytics, and business strategy, requiring both deep technical expertise and strong cross-functional influence. You will help unify data across the organization into trusted, governed, and reusable data products. This is a highly impactful position for someone who thrives in building foundational systems in fast-evolving environments.
Accountabilities:
Own and define enterprise data architecture strategy across conceptual, logical, and physical layers, ensuring scalable design across business domains such as finance, sales, product, and operations.
- Design and standardize modern data models and architecture patterns (dimensional, data vault, 3NF, lakehouse) to support analytics, BI, and operational workloads.
- Lead architecture for cloud data platforms (Snowflake, Databricks, Azure), ensuring optimal performance, scalability, cost efficiency, and reliability.
- Define and govern end-to-end data pipelines, including ingestion, transformation, integration, and serving layers across batch and real-time systems.
- Establish enterprise standards for data governance, metadata, lineage, security, and quality in collaboration with governance and compliance teams.
- Architect AI/ML-ready data ecosystems, including semantic layers, feature stores, RAG patterns, and governed data access for intelligent applications.
- Provide technical leadership across initiatives, guiding engineering teams from design to implementation and ensuring alignment with enterprise architecture principles.
- Act as a design authority in architecture reviews, ensuring consistency, scalability, and adherence to best practices across all data solutions.
Requirements:
Bring 10+ years of experience in data engineering, analytics, or related technical fields, with at least 5+ years in data architecture or solution architecture roles. Demonstrated expertise in designing and scaling enterprise-grade data platforms in cloud environments.
- Strong hands-on experience with modern data platforms such as Snowflake, Databricks, and Azure data services (Data Lake, Synapse, Azure SQL).
- Deep knowledge of data modeling approaches including dimensional modeling, normalized schemas, and data vault methodologies.
- Proven experience with ETL/ELT tools and frameworks such as dbt, Spark, or Azure Data Factory, along with CI/CD practices.
- Strong understanding of data governance, security, privacy, metadata management, and data quality frameworks.
- Experience enabling AI/ML workloads through data architecture, including feature engineering, semantic modeling, and real-time data access patterns.
- Excellent communication and stakeholder management skills, with the ability to translate complex technical concepts into clear business insights.
- Proven track record of influencing technical strategy and collaborating across engineering, analytics, and business teams in complex environments.
Benefits:
- Competitive base salary aligned with senior-level market benchmarks
- Comprehensive medical, dental, and vision insurance coverage
- Remote-first work flexibility
- 401(k) retirement savings plan with employer contribution options
- Employee stock purchase plan (where applicable)
- Paid time off and company holidays
- Professional development and continuous learning opportunities
- Inclusive culture with employee resource groups and collaboration communities
- Wellness and mental health support programs.