Data Architect

Roles & Responsibilities:

. Lead the data architecture design for core banking modernization initiatives

. Provides consultancy and advisory services for system integration, PoC, and impact analysis

. Conduct an in-depth analysis of system performance and identify any potential bottlenecks that may hinder optimal performance

. Effectively convey solution designs to diverse teams, and provide hands-on documentation or training sessions as necessary

. Define and implement data lake integration strategies to centralize and streamline data access

. Collaborate with cross-functional teams (Engineering, DevOps, Product, and Business) to align data models with business needs

. Design scalable, secure, and high-performance data pipelines and ETL frameworks

. Ensure data governance, lineage, and quality across all systems

. Evaluate and recommend modern data technologies, tools, and platforms

. Support migration from legacy systems to cloud-native or hybrid data platforms

. Create and maintain architecture documentation, standards, and best practices

Required Skills:

. Proven experience or certifications on the following skillsets - Messaging, container implementation, container orchestration, multi-tier application architecture, monitoring tools, and collaboration tools

. Experience in quotation of solutions, differentiating CAPEX and OPEX concepts and evaluating different options to find the most cost-effective solution

. A deep technical understanding required to source infra resources ranging from on-premises to cloud. Should be familiar with architect best practices, but also be flexible to adapt to the team's established practices and environment

. Good understanding of concurrent software systems and building them in a way that is scalable, maintainable, and robust

. Experience in various SQL and NoSQL databases (Oracle, MongoDB, Cassandra, PostgreSQL, MySQL)

. Proven experience in modernizing legacy banking systems and core banking platforms

. Strong expertise in data lake architecture (e.g., Azure Data Lake, AWS Lake Formation, Google BigLake)

. Hands-on experience with data modeling, ETL/ELT, and real-time data streaming(e.g., Kafka, Spark, Flink)

. Proficiency in SQL, Python, or Scala for data engineering tasks

. Familiarity with cloud platforms (Azure, AWS, GCP) and containerization (Docker, Kubernetes)

. Deep understanding of data governance, security, and compliance (e.g., MAS, GDPR, PCI-DSS)

. Experience working with banking data domains such as payments, loans, deposits, and customer 360

. Excellent communication and stakeholder management skills

Desired Skills:

. Excellent understanding of the solution design and vendor management

. Excellent understanding of the Agile development methodologies

. Good understanding of front to back system architecture - banking product lifecycles

. Effective written and verbal communication (Both English and Korean)