Senior Data Transformation Data Architect

The Digital Transformation Data Architect is responsible for designing, modernizing, and advancing the organization’s enterprise data ecosystem in support of strategic business objectives, regulatory requirements, and risk management practices. This role combines technical expertise with a forward-thinking mindset focused on building scalable, maintainable, and extensible data solutions that support current operations while enabling future innovation.

The ideal candidate is a hands-on architect and problem solver who balances speed of delivery with sound engineering principles. This individual will drive modernization efforts across data platforms, integration frameworks, analytics capabilities, automation initiatives, AI-enabled solutions, and risk modeling programs while ensuring solutions remain secure, compliant, reliable, and sustainable within a highly regulated financial services environment.

ESSENTIAL DUTIES AND RESPONSIBILITES include the following.

• 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., 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., This job description indicates the general nature and level of work expected of the incumbent. It is not designed to cover or contain a comprehensive list of activities, duties or responsibilities required of the incumbent. Incumbents may be asked to perform other duties as required.

Do you have experience in Technology security practices?, Do you have a Bachelor’s degree?, To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.

• 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.

EDUCATION and/or EXPERIENCE

• Expert-level SQL development and database optimization skills.
• Strong understanding of relational and dimensional data modeling techniques.
• Experience with SQL Server Integration Services (SSIS) and enterprise data integration frameworks.
• Experience with cloud-based data platforms such as Azure, AWS, Snowflake, Databricks, or equivalent technologies.
• Experience with Power BI, SSRS, or other business intelligence and analytics platforms.
• Experience with Python, machine learning frameworks, or AI-enabled data solutions preferred.
• Understanding of DevOps, source control, CI/CD, and automated deployment practices.
• Familiarity with data governance, metadata management, master data management, and data catalog solutions.
• Strong understanding of information security, data privacy, and regulatory compliance requirements., * Clear and effective communicator
• Attention to Detail: Produces accurate, high-quality work with strong follow-through.
• Strong Work Ethic, Accountability & Ownership: Demonstrates reliability, discipline, and responsibility for outcomes.
• Analytical & Critical Thinking: Evaluates complex problems, identifies root causes, and develops effective solutions.
• Risk-Based Mindset: Incorporates risk awareness into architecture, design decisions, and solution development.
• Collaboration & Influence: Builds strong relationships and works effectively across business and technical teams.
• Professionalism & Integrity: Demonstrates sound judgment and maintains high ethical standards.