Role overview
- A data modeler is a systems engineer who organizes raw data to make it easier to understand and process. The role will help data analysts understand trends, opportunities, and solutions to technical problems. This is will be accomplished through the use of modelling language or specific software. The role will be responsible for ensuring that their data is both structured and modelled effectively so that it can be used and understood.
Responsibilities and KRAs
- Work with the BIBAs to gather requirements for the database design and model
- Understand the data needs of the squads
- Collaborate with the development team to design and build the database model
- Engage the development team to implement the database
- Determine the business needs for data reporting requirements
- Adjust access to the data and the reports as needed
- Work closely with the engineering and architecture team to implement data warehouse and reporting
- Work with data scientists to determine metadata querying requirements
- Help determine and manage data cleaning requirements
- Help determine data security needs and implement security solutions
- Adopt the Enterprise Data Model as a standard for data model designs to leverage best practice and fast track data modelling efforts.
- Analyse and profile the source data to understand data quality issues , relationships, patterns and rules in the data.
- Facilitate dataflow understanding by collating dataflow diagrams outlining the flow of data across systems and interfaces.
- Reduce non value adding work by identifying opportunity for re-use of the Enterprise Data Model
- Maintain up to date knowledge of latest developments in the Data Modelling domain, including reading; continuous professional development courses; seminars and conferences.
- Seek opportunities to improve business processes, models and systems through agile thinking.
Requirements- Experience in Data Management role with understanding of data, risk, data architecture, data governance, data analysis, data validation and metadata management.
- Experience in banking and related regulatory/governance standards to provide high quality data having planned, implemented, integrated and controlled activities/processes to ensure availability, usability, integrity, compliance and security of data.
- Sound knowledge and understanding of data life cycle. Operational execution of data/metric standards and data quality rules.
- Understanding of and experience with root cause analysis and problem-solving skills and awareness of the Data Product Life Cycle (DPLC) & Agile methodologies.
- Extensive experience with Data Analysis, Data Integrity, Data Modelling, Data Warehouse layers and Metadata Qualifications
- Bachelors Degree in Computer Science or similar fields like Information Systems, Big Data, etc would be advantageous.
- AWS Data Engineer Certification would be advantageous
- Related Technical certifications
- Knowledge of Agile methodologies and project management practices, including Scrum, Kanban, and Lean
- Excellent communication, collaboration, and problem-solving
- Ability to work independently and in a team environment in an Agile framework
- Strong analytical and critical thinking skill
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