Job Description
JD:
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, AI/ML, or a related field
7+ years of experience designing, developing, deploying, and monitoring end-to-end data and analytics solutions
7+ years of experience in Data Warehouse and Data Lake architecture and development
5+ years of hands-on experience in data modeling and data architecture
Experience implementing at least one market-leading banking or financial services data model (e.g., Oracle, Teradata, IBM)
Strong understanding of data structures, data modeling, and data architecture principles
Strong architectural knowledge of analytics system patterns and their trade-offs
Excellent communication skills and ability to operate effectively in ambiguous environments
Technical Skills
Data modeling tools: ERwin, ER/Studio, SQL Modeler (preferred)
ETL/ELT frameworks, data pipelines, and data quality management
Relational and non-relational databases (e.g., Document DB, Graph DB)
Cloud-based data architectures, including security frameworks and governance tools
Metadata management, data lineage, and data quality frameworks
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, AI/ML, or a related field
7+ years of experience designing, developing, deploying, and monitoring end-to-end data and analytics solutions
7+ years of experience in Data Warehouse and Data Lake architecture and development
5+ years of hands-on experience in data modeling and data architecture
Experience implementing at least one market-leading banking or financial services data model (e.g., Oracle, Teradata, IBM)
Strong understanding of data structures, data modeling, and data architecture principles
Strong architectural knowledge of analytics system patterns and their trade-offs
Excellent communication skills and ability to operate effectively in ambiguous environments
Technical Skills
Data modeling tools: ERwin, ER/Studio, SQL Modeler (preferred)
ETL/ELT frameworks, data pipelines, and data quality management
Relational and non-relational databases (e.g., Document DB, Graph DB)
Cloud-based data architectures, including security frameworks and governance tools
Metadata management, data lineage, and data quality frameworks
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