Job description
Data Architect: JD: 1.
Building Bank EA tool with all Enterprise Architecture Artifacts 2.
Maintain and develop data collection, storage and transfer systems used by the project team 3.
Support development of advanced data analytics products 4.
Define data architecture and select data collection, storage and analysis technologies 5.
Control and check data availability, data completeness and quality, integration of external and internal data sources, application of analytical tools 6.
Manage and approve list of Critical Data Elements (CDEs) including providing domains with guidelines and support for prioritizing CDEs 7.
Business and Technical metadata management 8.
Establish, monitor and enforce business processes and standards for metadata management and compliance 9.
Provide the required support to IT team(s) in terms of the technical aspects related to data architecture and logical data models for the bank’s different systems and applications as well as the IT strategy in terms of data.
10. Define and maintain the logical data models and information assets 11.
Provide template for structuring business metadata (e.
g., business definitions, security/access levels, data quality rules) and technical metadata (e.
g., technical/physical data elements, data lineage) 12.
Approving changes to Metadata and managing new demand for Metadata 13.
Approve business definitions and data lineage developed by domains Define standards for metadata and ensure compliance Qualifications: • Bachelor’s degree, in Computer Science, Engineering, or Mathematics • Minimum of 3 years demonstrated a high degree of proficiency in designing and developing complex, high-quality analytical solutions • 3+ years of experience of Data platform implementation and Architecture • Experience + 7 years in n Technical Field and IT Field • Banking/Financial Background is preferred • Certifications: Relevant certifications like TOGAF, or similar are often preferred Expertise in database systems (SQL, NoSQL databases like MongoDB, Cassandra).
Strong knowledge of data warehousing solutions (e.
g., Snowflake, Amazon Redshift).
Experience with data modeling, data architecture design, and schema development.
Proficiency in ETL/ELT tools and processes.
Familiarity with cloud platforms (AWS, Azure, GCP).
Knowledge of big data technologies (Hadoop, Spark).
Experience Proven experience designing and implementing data architectures.
Experience working with data governance, data quality, and security.
Past roles involving data strategy, data integration, and infrastructure development.
Soft Skills Strong analytical and problem-solving skills.
Ability to communicate complex data concepts to non-technical stakeholders.
Leadership and project management capabilities.
This job post has been translated by AI and may contain minor differences or errors.
