As a Data Architect, you will be responsible for the design and evolution of the Group’s data platform and infrastructure. You will work closely with the firm’s technology and business architects to integrate our data storage and analytics infrastructure with existing Group systems and vendor solutions. Experience in the architecture of (commercial and open-source) software platforms and large-scale data infrastructures (preferably on cloud) is a must.
– Work closely with business owners, PM, business architects and data analysts; effectively translate business vision into data system architecture design and provide detailed technical review of vendor’s solution proposals;
– Continuously evolve the Group’s data architecture in an agile development approach while moving toward a target long-term architecture.
– Lead end-to-end implementation of prioritized projects, ensuring strategic fit, on-time delivery and optimized TCO
– Form a strong working relationship with IT architecture, infrastructure and operational teams in order to determine and agree on the further roadmap of the data analytics product.
– Collaborate with other application technology teams to ensure a coherent end to end implementation with existing Groups systems and platforms
– Support the build-out of data governance within the firm, following both domestic and international best market practices and regulations such as GDPR, PDPO etc.
– Take responsibility for the further development of our cloud migration strategy for data.
– 8-10+ years of working experience with designing and implementing large scale enterprise data lake or warehouse and BI projects supporting 100+ TB data size
– 5+ years of architectural design experience in the financial industry
– 3+ years of working experience with incorporating structured data processing with non-structured or semi-structured data processing by applying various data technologies
– Master’s degree or above in computer science, electrical engineering or related majors
– Good programming skills in SQL, scripting languages, and at least one high-level programming language (e.g. Python)
– Deep understanding of traditional RDBMS, DW, BI concepts and design methodologies as well as modern data science and AI & machine learning technologies
– Experience with big data analytic tools including Apache Hadoop, Spark, Flink, Kafka, ELK and others in addition to traditional data warehouses to fulfill business requirements
– Excellent communication and problem-solving capabilities
– Deep understanding of container technologies such as Openshift, K8s, Docker and Kubernetes. Excellent performance tuning skills by applying various skills, such as storage planning, caching, index design, data partitioning, MPP, etc.
– Experience of using TOGAF or other architectural frameworks
– Documented experience from event-driven architecture
– Familiar with Site Reliability Engineering Concept, experienced in Infrastructure and Configuration as Code
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