the role owner is expected to design, implement, and document data architecture, data modeling and data collaboration solutions, which include the use of relational, dimensional, and NoSQL databases to support enterprise data management, business intelligence, machine learning, data science, and other data related initiatives.
Identification of banks critical data assets and related attributes.
Ensure all solutions designed and deployed in the bank space to conform to required data standards and quality requirements.
Analyze structural data requirements for new software and applications.
Develop migration plans of data from legacy systems to new solutions.
Design and support a robust data architecture that supports data collaboration, reusability and quality improvement.
Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and machine learning).
Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models.
Ensure proper controls/tools are in place to maintain data integrity across the bank.
Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.
Work proactively and independently to address data related project requirements and articulate design/modelling issues/challenges to reduce delivery risks.
Ensure all data integrity challenges across the bank are properly identified, documented and resolved timely.
Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices.
Engage with users during development and testing activities for data relates solutions.
Conceptualize, execute, and refine design specifications in the form of process flows, information architecture, wireframes, prototypes, and functional design specs.
Understand complex customer data, business goals, requirements, and translate them into functional and technical designs.
Guide initiatives of data solutions designs and development.
Guide Data Integrations and Modelling Specialists in development of stored procedures to create data targets that have been refined and meet required data standards
Experience, Knowledge and Skills Requirements
Bachelor’s Degree in Computer/Data Science technical or related field.
At least 3 years of enterprise data systems design and development experience.
Minimum 3 years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
Experience with data management and relational database design and familiarity with data formats, table joins, and ETL.
Experience in data quality analysis, data governance and modelling techniques.
Experience in data related enterprise platforms.
Experience in financial services especially in banking preferred.
Advanced level proficiency in Structured Query Language (SQL).
Good knowledge of metadata management, data modeling, and related tools (Erwin or ER Studio or others).
Strong analytical, documentation and problem solving skills.
Strong business analysis skills and project management methodologies.
Knowledge in data architecture, data warehousing, master data and metadata management, enterprise information integration and ETL using a cross section of technologies and programming languages
Clear understanding of common data requirements as they relate to the finance, sales, corporate, retail, marketing etc.
Understands the impact of strong data governance in addressing data quality and integrity issues.
In-depth understanding of database structure principles.