Data Solution Architect (Buffalo)

The Data Solution Architect is responsible for designing and delivering enterprise-grade data platforms and solutions that enable advanced analytics and business intelligence. This role requires deep expertise in data engineering, cloud-native architecture, and modern data technologies. The architect will work closely with engineering, product, and compliance teams to build secure, scalable, and regulatory-compliant data solutions. All solutions must align with the principles, standards, and reference architectures established by the Enterprise Architecture function, ensuring consistency, interoperability, and strategic fit across the organization.

Key Responsibilities

• Solution Architecture : Architect and deliver cloud-based data platforms (e.g., Azure Data Lake) and scalable data pipelines using technologies such as Databricks, Kafka, etc.
• ETL / ELT Frameworks : Develop and implement ETL / ELT frameworks for ingesting, transforming, and integrating data from diverse sources, including legacy financial systems, SaaS platforms, and real-time data streams.
• Data Platform Deployment : Design and oversee deployment of data warehouses, lakehouses, and analytics sandboxes to support business intelligence, machine learning, and reporting needs inclusive of Power BI and Snowflake.
• Data Governance : Define and enforce data governance, metadata management, and data quality standards in accordance with Enterprise Architecture guidance and regulatory requirements.
• Enterprise Architecture Collaboration : Collaborate with Enterprise Architecture to ensure all solutions adhere to architectural standards, reference models, and technology roadmaps.
• Technology Evaluation : Lead technical evaluations and proof-of-concept projects for emerging data technologies (e.g., real-time analytics, data mesh, AI / ML platforms).
• Technical Documentation : Produce deliverables such as architecture diagrams, data flow maps, security models, and technical documentation for solution handoff and operational support.
• Agile / DevOps Leadership : Guide Agile / DevOps teams in implementing CI / CD pipelines, automated testing, and infrastructure-as-code for data solutions.

Expected Skills

Expected Knowledge

Qualifications

Expected Deliverables

This role combines technical depth with strategic vision to build data platforms that bridge traditional finance and modern analytics ecosystems. The ideal candidate will balance innovation with operational rigor to deliver secure, compliant, and user-centric data solutions.