About the job
The Senior Data Architect - AWS spearheads innovative data and analytics initiatives, focusing primarily on AWS cloud platforms. This pivotal role entails architecting, implementing, and overseeing enterprise-level data solutions, advanced analytics platforms, and machine learning infrastructure. The ideal candidate will be a data thought leader, crafting scalable, secure, and high-performance architectures that enhance business value through actionable insights and intelligent automation.
Key Responsibilities:
- Data Architecture & Strategy: Develop and implement the enterprise data architecture strategy, establishing architectural standards and best practices for data lakes, warehouses, and streaming analytics. Lead modernization roadmaps for transitioning legacy systems to cloud-native AWS architectures.
- Platform Leadership: Direct the AWS data platform architecture, including Lakehouse and Data Mesh patterns, along with metadata management and data lineage. Design scalable data ingestion pipelines and processing frameworks utilizing tools such as Glue, EMR, and Step Functions.
- Machine Learning & MLOps: Create and execute end-to-end ML platforms and MLOps frameworks using Amazon SageMaker. Architect scalable inference solutions and automate ML pipelines for reproducible, version-controlled workflows.
- Cross-Platform Integration: Design hybrid and multi-cloud solutions that connect AWS with Azure and on-premises systems. Develop unified data access patterns and federated query capabilities.
- Governance & Security: Establish comprehensive data governance and security frameworks, including encryption, fine-grained access control, and automated data quality validation pipelines. Ensure compliance with regulatory standards such as GDPR and CCPA.
- Team Leadership: Build and mentor high-performing teams of data and ML engineers. Conduct architecture reviews and collaborate with data scientists and business stakeholders to translate analytical requirements into robust technical solutions.

