Principal AI Data Architect/Principal Data Integration Architect
New York, New York, United States of America
Contract
1 week ago
Key skills
AIMLData EngineeringData LakeSnowflakeDatabricksKafkaAWSAzureGoogle CloudK8sServerlessService Mesh
About this role
* 8+ years of experience in Data architecture and engineering, distributed systems and/or platform architecture.
* Deep hands-on experience with modern cloud providers like AWS, Azure or Google Cloud Platform and AI/ML technology stack (including but not limited to LLMs, MCPs, K8s, Open AI, Snowflake, Databricks etc.)
* Deep hands-on experience with modern cloud providers like AWS, Azure or Google Cloud Platform and modern platforms like Snowflake, Databricks, Azure data lake, Lakehouse architectures and Data lakes or equivalent.
* Deep knowledge about various distributed data storage formats like Iceberg, ORC, Parquet etc.
* Strong understanding of Data Engineering and Data Governance, Data Lineage and Privacy frameworks.
* Experience in providing clear guidance on data cataloging, metadata policies, adoption and frameworks.
* Ability to break / decouple data ecosystems into clear capabilities, standards and integration patterns.
* Knowledge of AI/ML platform integration is a huge plus.
* Prior experience in Platform Engineering and building horizontal shared or central capabilities.
For Principal Data Integration Architect
* 8+ years of experience in software architecture and engineering.
* Hands-on experience with major cloud providers like AWS, Azure or Google Cloud Platform and modern platforms like Service Mesh, Observability stacks, Kafka, Serverless, K8s etc.
* Exceptional ability to decouple complex systems into coherent logical building blocks, capabilities and integration contracts.
* Experience working in enterprise and/or federated architecture environments with multiple complex domains.
* Prior experience in Platform Engineering and building horizontal shared or central capabilities.
* Experience driving cross-domain alignment in complex organizations.
* Deep knowledge about cloud compliance, DevOps models, security, data and AI integration points.
* Expert in building and architecting distributed systems with end-to-end integration and observability.