Enterprise Data Architect

Job Description

We are seeking a highly experienced and strategic Enterprise Data Architect to lead and shape the bank's enterprise-wide data architecture and digital transformation initiatives. This leadership role is responsible for defining and implementing scalable, secure, and future-ready data strategies that support business growth, AI/ML innovation, regulatory compliance, and enhanced customer experiences

Key Responsibilities:

• Define and maintain the enterprise data architecture strategy and roadmap aligned with business objectives and digital transformation goals.
• Design and govern scalable, secure, and high-performance data architectures across the full data lifecycle.
• Establish and enforce data governance, quality, security, metadata management, and data lineage standards in compliance with banking regulations.
• Lead modernization of enterprise data platforms and integrate cloud-native technologies, Customer Data Platforms (CDP), and advanced analytics capabilities.
• Architect and optimize data pipelines to support AI/ML model development, deployment, and advanced analytical initiatives.
• Collaborate with senior leadership and cross-functional teams to drive data-centric decision-making and promote data literacy across the organization.
• Mentor and guide data engineering and architecture teams while providing strategic technology leadership.

Applicant Profile:

• Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or a related field.
• Minimum 10 years of experience in data architecture, including at least 5 years in an enterprise-level role within the financial services sector.
• Strong expertise in enterprise data modelling, data governance frameworks, and data quality management.
• Deep understanding of modern data architecture concepts including data lakes, data warehouses, data marts, Data Mesh, and Data Fabric.
• Hands-on experience with cloud-based data platforms, especially Google Cloud technologies such as BigQuery, Dataflow, and Pub/Sub.
• Strong knowledge of Hadoop ecosystem tools including HDFS, Hive, and Spark.
• Experience with SQL, NoSQL, ETL pipelines, scripting languages (Python/Scala), data virtualization platforms, and enterprise ML platforms.
• Proficiency in Bl and reporting tools such as Tableau, Looker, or similar visualization platforms.
• Familiarity with banking regulatory requirements and data security best practices.
• Excellent communication, stakeholder management, and leadership skills with the ability to guide technical teams and present complex concepts to diverse audiences.