Platform Architect

Job Title: Platform Architect – Customer Data Program Department: IT and Data Analytics Employment Type: Full-time | On-site / Hybrid (as applicable) Job Summary The Platform Architect under the Customer Data Program is responsible for designing and optimizing scalable, secure, and high‑performant data and analytics platforms that support enterprise‑wide digital and AI initiatives. This role serves as the technical authority for solution architecture, ensuring integration, governance, and performance alignment with the organization’s enterprise architecture. The ideal candidate must have hands‑on experience in Informatica MDM and Informatica DEI, strong expertise in Azure data services, and a proven ability to architect end‑to‑end data platforms that enable analytics, reporting, and AI solutions. Key Responsibilities Design scalable, secure, and high‑performance data solutions leveraging Azure services such as Azure Data Factory, Azure Databricks, Azure Data Lake, and related components. Develop and maintain architecture frameworks and patterns to support the adoption of an Enterprise Data Platform and AI Platform for analytics, reporting, and generative AI solutions. Ensure that all data platform designs comply with the bank’s Enterprise Architecture guardrails and overall technology roadmap. Oversee the architecture, design, and optimization of the bank’s Master Data Management (MDM) platform using Informatica MDM. Collaborate with cross‑functional teams to integrate data lineage, governance processes, and data quality into all solution designs. Platform Performance Optimization Optimize ETL processes and data pipelines for performance, scalability, and cost efficiency. Provide technical expertise in troubleshooting and performance tuning, ensuring high availability and reliability of the platform. Implement best practices for cloud cost management, data query optimization, and scalability strategies. Stakeholder Collaboration Partner with data platform owners, enterprise and solution architects, business stakeholders, and delivery teams to align solutions with business goals and technical standards. Communicate architectural decisions, risks, and recommendations effectively to both technical and non‑technical stakeholders. Lead proof‑of‑concept initiatives to evaluate emerging tools, technologies, and methodologies in data analytics and AI. Champion the adoption of generative AI and other emerging data technologies aligned with the organization’s strategic goals. Drive continuous improvement in architecture design, performance, and development processes in compliance with SDLC best practices. Qualifications Education Bachelor’s degree in Information Technology, Computer Science, Engineering, or a related discipline. Master’s degree or relevant certifications (e.g., Microsoft Certified: Azure Solutions Architect Expert, Informatica Certified Professional, or TOGAF) is an advantage. Experience Minimum of 8–10 years of experience in data platform architecture, solution design, or enterprise data management within large‑scale IT organizations. Must have strong hands‑on experience with Informatica MDM and Informatica Data Engineering Integration (DEI), including design, configuration, and optimization. Experience architecting data integration, data governance, and analytics solutions for enterprise environments (preferably in banking, financial services, or telecommunications). Solid understanding of data modeling, data lineage, and metadata management principles. Technical Skills Performance Optimization: Cloud cost management, data query tuning, and scalability engineering. Automation & CI/CD: Experience implementing DevOps practices for automated deployment and environment management. Data Governance: Familiarity with policies and frameworks for data quality, lineage, and security compliance. Soft Skills & Core Competencies Strategic Thinking: Ability to align platform strategies and architecture decisions with business objectives. Leadership: Provide guidance and mentorship to technical teams, fostering a collaborative engineering culture. Problem‑Solving: Lead resolution of complex data platform challenges with structured, innovative solutions. Communication: Communicate complex technical concepts clearly to stakeholders at all organizational levels. Stakeholder Management: Build strong relationships across IT, business, and vendor teams to drive alignment. Mentorship: Coach and develop team members to strengthen organizational technical capability. Adaptability: Stay abreast of emerging technologies and incorporate them effectively into architectural strategies. #J-18808-Ljbffr