Own the architecture for cloud-native data platforms, including Lakehouse designs (Delta Lake, Iceberg, Databricks, or Microsoft Fabric) that support reporting, analytics, and BI
Design scalable data models supporting enterprise platforms, including ERP, financial, operational, and project management systems
Lead modernization initiatives for legacy data environments, including migration strategy, data mapping/transformation, reconciliation, and cutover to production
Build frameworks for real-time and near real-time data ingestion and processing, alongside batch pipelines (ELT/ETL)
Drive decisions across storage, orchestration, data quality, reliability, and performance
Define semantic data models that enable self-service analytics and consistent reporting, in coordination with data governance, metadata management, and master data management (MDM) standards
Partner with business and technical stakeholders across functional areas to prioritize requirements and translate them into architectural decisions
Support secure, governed data access in coordination with Identity and Access Management (IAM) teams
Evaluate emerging technologies, including AI, and identify opportunities to apply them within the data ecosystem; help shape the long-term technical roadmap
Mentor junior architects and data management staff, and translate complex technical concepts into clear, business-friendly language for technical and non-technical audiences alike

8+ years of experience in data architecture, data modeling, or cloud data engineering
Hands-on experience designing and implementing cloud data solutions using Snowflake, Azure, AWS, and/or Databricks
Deep understanding of distributed systems, data architecture, and modern cloud infrastructure
Experience with Lakehouse architecture and platforms (Delta Lake, Apache Iceberg, Apache Hudi)
Demonstrated success designing semantic data models for reporting and analytics at scale
Experience leading or supporting large-scale data migrations, from discovery through cutover, and building systems from concept through production
Strong grounding in modern data warehousing, ELT/ETL, and cloud architecture best practices
Proven ability to navigate ambiguity, influence technical direction, and drive clarity across cross-functional teams

Cloud Data Architect

Key skills