Data Solution Architect, AWS

We are seeking a Data Solution Architect, AWS, to lead data pipeline design and implementation for a cloud-native analytics and GenAI-enablement initiative, owning architecture decisions across data ingestion, transformation, storage, and search/retrieval infrastructure using AWS services.

Responsibilities

• Design and architect scalable data pipelines using AWS Glue for ETL orchestration, Lambda for event-driven processing, and S3 for data lake storage
• Define data architecture patterns aligned with AWS Well-Architected Framework principles for reliability, performance, and cost optimization
• Create technical specifications and architecture diagrams for data platform components
• Lead development of Python and PySpark solutions for large-scale data processing and transformation
• Architect OpenSearch and vector database solutions to support semantic search, retrieval-augmented generation, and AI/ML workloads
• Design data models and pipelines that enable advanced analytics including regression analysis and NLP applications
• Provide architectural guidance on GenAI strategy, advisory, and operational integration with existing data infrastructure
• Design infrastructure patterns that support machine learning model training, inference, and deployment workflows
• Advise on data preparation and feature engineering approaches for ML/AI use cases
• Establish CI/CD patterns for data pipeline deployment and infrastructure-as-code practices
• Collaborate with engineering teams to ensure data platform components meet operational excellence standards
• Support knowledge transfer and technical documentation for sustained delivery

Requirements

• 7+ years of experience in data analytics engineering
• High proficiency in PySpark
• Advanced expertise in AWS Glue, AWS Lambda, and Amazon S3
• Proven skills in Amazon OpenSearch
• English proficiency at B2 level or higher

Nice to have

• Knowledge of machine learning
• Familiarity with CI/CD
• Understanding of vector databases