Data Architect

We are looking for an experienced Data Architect to design and enhance modern data solutions for a banking environment in Needham, Massachusetts. This role focuses on building scalable cloud-based data architecture, improving data movement and transformation processes, and enabling reliable access to business-critical information. The ideal candidate brings strong expertise in Azure, Snowflake, Python, and Spark, along with a practical approach to data modeling, integration, and performance optimization.

Responsibilities:
• Design and maintain enterprise data architecture that supports secure, scalable, and efficient data operations across banking platforms.
• Build and optimize ETL pipelines to ingest, transform, and deliver data from multiple sources into cloud-based analytical environments.
• Develop robust data solutions using Azure services, Snowflake, Python, and Apache Spark to meet business and reporting needs.
• Create data models and architectural standards that improve consistency, accessibility, and long-term maintainability of data assets.
• Partner with engineering, analytics, and business teams to translate data requirements into reliable technical solutions.
• Monitor data platform performance and implement improvements that strengthen processing speed, quality, and system reliability.
• Establish best practices for data governance, documentation, and architecture design to support regulatory and operational expectations.
• Troubleshoot complex data issues and provide technical guidance on integration, transformation, and storage strategies.• 7+ years of experience in data architecture, data engineering, or a closely related technical role.
• Strong hands-on experience with Microsoft Azure and Windows Azure services for cloud-based data solutions.
• Proven expertise in Snowflake for data warehousing, optimization, and large-scale data management.
• Proficiency in Python and Apache Spark for data processing, transformation, and workflow development.
• Solid background in ETL design, implementation, and support for enterprise data environments.
• Experience designing scalable data models and integrating structured and unstructured data sources.
• Ability to work effectively in a regulated industry such as banking or financial services is preferred.