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The Data Program Architect is responsible for defining and driving the architecture vision, strategy, and execution of the enterprise data platform for the Ascensus Government Savings division. This role owns critical architectural decisions across data storage, integration, access patterns, and tooling, and plays a central role in shaping the data platform roadmap in collaboration with product, business, and technology leaders.

This is a highly visible leadership position that requires strategic thinking, strong technical judgment, and proactive engagement across the organization. Success in this role depends on the ability to clearly communicate complex data concepts, build trusted relationships, and influence outcomes that align technology with business goals.

Section 1: Position Summary

The Data Program Architect brings a deep understanding of core business domains and data flows, paired with broad technical expertise across Oracle databases, Azure-based data warehouses, ETL and integration platforms, and secure data access patterns. This role ensures the data platform delivers scalable, compliant, and high-quality data in support of critical product initiatives, analytics, and operational needs.

Acting as a senior architectural leader, the Data Program Architect collaborates closely with scrum teams, enterprise architects, security, infrastructure, and operations partners to research, design, socialize, and review data solutions. The role establishes reference architectures and best practices, assesses platform health and technical debt, and guides effective, standards-aligned execution across teams.

Section 2: Job Functions, Essential Duties, and Responsibilities

• Define and own the end-to-end data platform architecture for Ascensus Government Savings, including vision, strategy, standards, and execution across operational, analytical, and integration layers, ensuring scalability, regulatory compliance, and secure data access.

• Lead architectural design for enterprise data systems, including Oracle-based transactional platforms, Azure-based data warehouses, and downstream analytics and reporting solutions; guide logical and physical database designs to support performance, resiliency, and extensibility.

• Own data platform tool and technology selection, including data warehouses, ETL and integration tools (e.g., Informatica), orchestration frameworks, and data access methods; conduct due diligence, assess vendor and cost tradeoffs, and ensure alignment with enterprise and cloud strategies.

• Define and govern secure, consistent, and performant data access patterns and APIs, including MCP- or server-based designs, supporting internal applications, analytics users, and approved external consumers.

• Provide architectural oversight and execution guidance to data and delivery teams, translating high-level architecture into actionable designs and partnering with engineers to balance standards compliance with timely delivery.

• Partner with product, business, and technology leadership to shape the data platform roadmap, ensuring architectural decisions directly support business outcomes, regulatory requirements, analytics needs, and future growth.

• Establish and maintain reference architectures and design standards for data ingestion, transformation, storage, access, and governance, enabling reuse, consistency, and reduced technical debt.

• Oversee the overall health of the data platform portfolio, including scalability, performance, stability, cost efficiency, risk exposure, and technical debt; collaborate with stakeholders to prioritize remediation and investment initiatives.

• Promote collaboration and architectural transparency across engineering, security, infrastructure, database, risk, support, and operations teams; serve as a trusted enterprise-level architectural advisor.

• Drive innovation and continuous improvement in data architecture, tooling, and processes by evaluating emerging technologies and patterns relevant to fintech and cloud-native data platforms.

• Provide hands-on technical leadership and mentorship, guiding engineers and architects on best practices in data modeling, ETL design, cloud data patterns, and secure data access.

• Ensure data security, privacy, and compliance by design, working closely with security and risk teams to prevent unauthorized access, improper transmission, or unapproved disclosure of regulated data.

• Exercise broad technical autonomy and judgment, making architecture and design decisions with significant business impact while aligning to enterprise principles and governance.

Section 3: Experience, Skills, and Knowledge Requirements

• 15+ years of experience in Information Technology, with significant experience in data architecture and enterprise data platform design; experience in financial services or fintech environments strongly preferred.

• Deep expertise in enterprise data architecture, including transactional and analytical platforms that support scale, regulatory compliance, and governed data access.

• Strong background in data engineering and platform design, with hands-on experience architecting and guiding implementations across ingestion, transformation, storage, and access layers; ability to contribute to proofs of concept as needed.

• Extensive experience with Oracle databases, including data modeling and performance considerations for operational systems.

• Proven experience designing Azure-based data warehouse solutions, including modern cloud architectures, performance tuning, cost optimization, and analytics integration.

• Hands-on experience with ETL and data integration architectures, including significant experience with Informatica or similar tools; strong understanding of batch and near-real-time data movement, orchestration, and data quality patterns.

• Experience defining and governing data access methods, including server-based designs (e.g., MCP or similar patterns), ensuring secure and consistent access across applications and consumers.

• Ability to develop a deep understanding of business capabilities and data domains and partner effectively with product, analytics, risk, and business leaders to align data architecture with strategy.

• Strategic mindset paired with strong execution skills; ability to balance long-term architectural vision with near-term delivery needs.

• Strong leadership and influence skills, with the ability to build trust, mentor engineers and architects, and drive alignment across cross-functional teams without direct authority.

• Excellent communication and executive-level presentation skills, including the ability to clearly explain complex technical concepts to non-technical audiences.

• Experience with distributed systems and integration patterns, including service-oriented architectures, event-driven platforms, and data-driven microservice ecosystems.

• Strong understanding of data security, privacy, and compliance, including authentication, authorization, and secure handling of sensitive and regulated data.

• Innovation-oriented mindset, comfortable challenging existing approaches and introducing new architectural patterns, tools, and practices.

• Demonstrated passion for continuous learning and staying current with emerging trends in cloud data platforms, analytics, integration, and data architecture.