Enterprise Data Architect - Commercial Bank Colombo

About the job

Job Profile:

• Strategic Data Vision & Roadmap: Define, evolve, and maintain the bank's enterprise data architecture strategy and roadmap, aligning it with business objectives, digital transformation, and regulatory requirements. Provide thought leadership on emerging data technologies and best practices.
• Architecture Design & Governance: Design and oversee scalable, secure, and high-performance data architectures across the entire data lifecycle. Establish and enforce data architecture standards, guidelines, and principles, ensuring data governance, quality, metadata management, lineage, and security in compliance with regulations.
• Platform Modernization & Integration: Drive the architectural evolution and optimization of our data platforms, strategically leveraging our existing ecosystem and leading the deeper integration of the CDP platform. Architect robust data pipelines and seamlessly integrate capabilities.
• AI/ML & Advanced Analytics Enablement: Architect data solutions to efficiently support the development, training, deployment, and monitoring of AI/ML models. Ensure data readiness and accessibility for all advanced analytical initiatives.
• Leadership & Collaboration: Act as a trusted advisor to senior leadership and cross-functional teams, leading and mentoring data engineering and architecture teams. Drive cultural change towards data-centric decision-making and promote data literacy across the bank.

Applicant Profile:

• Bachelor's or master’s degree in computer science, Data Science, Information Systems, or a related quantitative field.
• 10+ years of progressive experience in data architecture, with at least 5 years in an enterprise-level role within a financial services institution (highly preferred).
• Demonstrable expertise in designing and implementing large-scale data platforms, including experience with:
• Cloud Data Platforms: Deep hands-on experience with Google Cloud Platform (GCP), particularly Google Big Query, Google Cloud Storage, Dataflow, Pub/Sub, and other relevant data services.
• Big Data Ecosystems: Strong understanding of Apache Hadoop ecosystem components (HDFS, Hive, Spark, etc.).
• Data Virtualization: Experience with Denodo is a significant advantage.
• ML Platforms: Practical experience with VertexAI or other enterprise-grade ML platforms.
• BI & Reporting Tools: Proficiency with Tableau and Looker.
• Customer Data Platforms (CDP): Experience with Resulticks or similar CDP platforms is a plus.
• Proven track record of defining and implementing enterprise data models, data governance frameworks, and data quality initiatives.
• Strong understanding of data warehousing, data lakes, data marts, and modern data architecture patterns (e.g., Data Mesh, Data Fabric).
• Expertise in SQL, NoSQL databases, data modeling tools, ETL processes & data pipelines, and scripting languages (e.g., Python, Scala).
• Familiarity with regulatory compliance in banking data management and security best practices.
• Excellent communication, presentation, and interpersonal skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
• Strong leadership capabilities with experience in mentoring and guiding technical teams.