Data Architect

Job Location: Pune & Bangalore

Role Description:

We are seeking a highly skilled and experienced Data Architect to join Corporate Security team. This critical role will be instrumental in shaping the data strategy for key business domain within the bank, ensuring robust, reliable, and compliant data practices. The successful candidate will possess a deep understanding of banking data ecosystems, regulatory requirements, and cutting-edge data architecture principles. Responsible for defining the future state of data within their assigned domains, driving initiatives that enhance data quality, accessibility, and strategic value. This role requires a strong blend of technical expertise, strategic thinking, and excellent communication skills to collaborate effectively with various stakeholders across the organization. Play as technical support for our security data ecosystem, architecting a unified GCP-based data platform that serves as the backbone for middleware, AI-driven insights, and enterprise-wide reporting.

Key Responsibilities:

- Data Blueprinting & Modeling: Develop conceptual, logical, and physical data models for the PIAM domain to support complex Role-Based Access Control (RBAC). - Integration Architecture: Design the architecture for a data middleware platform on GCP to orchestrate real-time feeds, system integrations, and multi-source data synchronization. - Data Identification: Audit and identify all critical internal and external physical security data sources, from badge readers to global visitor management systems. - Strategy & Alignment: Publish a technical data strategy that directly aligns with the organization’s enterprise data sourcing framework and governance standards. - Platform Decision-Making: Evaluate and select the appropriate GCP stack (e.g., Big Query, Dataflow) for feed generations, automated reporting, and advanced analytics. - AI & Intelligence Design: Engineer data structures specifically optimized for AI/ML insights to detect access anomalies and security risks

Skills & Experience:

- Minimum 8+ years of experience in data architecture, data modeling, or a related data-centric role within the financial services industry, preferably banking. - Prior experience as a senior engineer, architect, or senior business/technical analyst, designing and implementing complex systems, platforms and services. - Expertise in data modeling methodologies (e.g., conceptual, logical, physical) and tools (e.g., Power Designer, Sparx Enterprise Architect). - Strong knowledge of data warehousing concepts, ETL/ELT processes, and data integration patterns. - Hands-on experience with modern data platforms such as data lakes (e.g., Hadoop, S3), data warehouses (e.g., Snowflake, Teradata, Azure Synapse, Google Big Query), and real-time data streaming (e.g., Kafka). - Proficiency in SQL and experience with various database technologies (relational, NoSQL). - Familiarity with data governance frameworks and data quality management principles. - Understanding of regulatory requirements impacting data within financial services (e.g., BCBS 239, GDPR, CCPA, AML, KYC). - Experience with cloud-based data solutions (AWS, Azure, GCP) is highly desirable. GCP is good to have as primary skill set. - Experience in transformation programs, including representing architecture or delivery in senior stakeholder and governance forums. - Strong written and oral communication skills to diverse audiences to build consensus, share and drive architecture and strategy, with senior management and our global engineering delivery team. - Understanding principles of Information Security. - Proven experience in defining and implementing data strategies for complex organizations. - Deep understanding of banking data domains such as retail banking, investment banking, risk, finance, treasury, payments, and customer data. - Excellent analytical, problem-solving, and critical thinking skills. - Strong communication, presentation, and interpersonal skills with the ability to articulate complex technical concepts to both technical and non-technical audiences. - Ability to work independently and collaboratively in a fast-paced, dynamic environment.

Good to Have:

- AI/ML Experience: Deploying AI-driven security insights or predictive threat modeling. - Certifications: Professional certifications such as Certified Data Management Professional (CDMP) or Google Cloud Professional Data Engineer. - Middleware Knowledge: Familiarity with building or managing integration platforms and API-led middleware architecture. - CSO Exposure: Prior experience working directly within or supporting a Chief Security Office in a global enterprise.

Qualifications:

- Bachelor’s degree in computer science, Information Systems, Engineering, Mathematics, or a related quantitative field. - Master's degree in a relevant field is a plus. - Relevant industry certifications (e.g., Certified Data Management Professional (CDMP), Cloud Data Architect certifications) are a significant advantage.