Senior Data Transformation Architect

Role Overview

• Design, develop, and maintain enterprise data architecture solutions that support business growth, operational efficiency, regulatory compliance, and risk management objectives.
• Lead modernization initiatives across data platforms, integration frameworks, reporting environments, and analytical capabilities.
• Evaluate and implement emerging technologies, including cloud services, artificial intelligence, machine learning, automation, and advanced analytics solutions where appropriate.
• Architect scalable and reusable data integration frameworks that reduce maintenance overhead and support future business expansion.
• Develop and optimize ETL/ELT processes, data pipelines, and data movement strategies across multiple systems and platforms.
• Collaborate with business leaders, risk management teams, compliance personnel, and technology stakeholders to translate business requirements into sustainable technical solutions.
• Design data models, metadata strategies, governance frameworks, lineage tracking, and quality controls that support enterprise reporting and regulatory requirements.
• Partner with stakeholders to identify opportunities for process automation, operational improvement, and enhanced decision-making through data-driven solutions.
• Establish and promote development standards, architectural best practices, and data engineering disciplines that balance agility with long-term maintainability.
• Evaluate existing systems and processes to identify technical debt, scalability limitations, operational risks, and modernization opportunities.
• Support risk modeling, forecasting, financial analytics, and strategic reporting initiatives through robust data architecture and engineering practices.
• Implement monitoring, validation, reconciliation, and control processes to ensure data accuracy, integrity, availability, and auditability.
• Participate in technology roadmap planning and provide architectural guidance for future-state platform evolution.
• Serve as a technical leader and trusted advisor across multiple business and technology teams.
• Maintain awareness of regulatory expectations, industry trends, cybersecurity considerations, and emerging technologies impacting financial services organizations.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Data Science, Mathematics, Finance, or related field; equivalent combination of education and experience will be considered.
• 5+ years of experience designing, developing, and supporting enterprise data solutions.
• 5+ years of experience in financial services, banking, fintech, insurance, or other highly regulated environments preferred.
• Advanced experience with Microsoft SQL Server, T-SQL, data modeling, database design, and performance tuning.
• Strong experience developing and supporting ETL/ELT processes using SSIS or comparable integration technologies.
• Demonstrated experience designing scalable and reusable data architectures that support long-term business growth and evolving requirements.
• Experience leading or significantly contributing to data modernization initiatives.
• Experience implementing data governance, data quality, lineage, reconciliation, and audit controls.
• Experience supporting enterprise reporting, analytics, forecasting, risk management, or financial modeling initiatives.
• Proven ability to translate complex business requirements into sustainable technical solutions.
• Experience evaluating and implementing emerging technologies including cloud platforms, AI, machine learning, automation, and advanced analytics solutions.

Tech Stack

• Cloud
• Cyber Security
• ETL
• MS SQL Server
• SQL
• SSIS

Benefits

• This job does not have managerial responsibilities. However, the position is expected to provide technical leadership, mentorship, architectural guidance, and influence across project teams and stakeholders.