Data Architect

Description

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.

Requirements

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.

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