Data Modeler Responsibilities:
- As a data modeler, you will be responsible to understand and translate business needs into data models supporting long term solutions.
- Responsible for working with the Application Development team to implement data strategies, build data
flows and develop conceptual data models.
- Recognize the need for a specific relational design (OLTP, OLAP) from a set of requirements.
- To create logical and physical data models using best practices to ensure high data quality and reduced redundancy.
- Optimize and update logical and physical data models to support new and existing projects.
- To Maintain conceptual, logical and physical data models along with corresponding metadata.
- Develop best practices for standard naming conventions and coding to ensure consistency in data models.
- Recommend opportunities for reuse of data models in new environments.
- Perform reverse engineering of physical data models from databases and SQL scripts.
- Evaluate data models and physical databases for variances and discrepancies.
- Validate business data objects for accuracy and completeness.
- Analyze data-related system integration challenges and propose appropriate solutions.
Data Modeler skillset requirements:
- 5+ years of professional experience as a Data Modeler.
- Experience in Financial Services and specifically within data domains / functions (e.g. Data Management, Data Architecture, Data Governance).
- Experience in data modeling tools like Erwin, Visual Paradigm, ER Studio
- Experience in Dimensional data modeling, Entity Relationship (ER) data modeling.
- Good experience with at least one cloud platform like AWS or GCP or Azure.
- Experience using Database platforms like Oracle, SQL Server, Teradata.
- Demonstrable knowledge of Data Management tools and techniques.
- Experience in eliciting, documenting, and verifying requirements for the use of data across the organization (Global Businesses and Functions) as appropriate to project scope.
- Experience in working within large, complex, and geographically dispersed projects, including different time zones.
- Previous experience as a data analyst, solutions analyst, or architect including delivery of data artifact (e.g. data models, data flow diagrams, metadata) would be beneficial.
- Proven strength in conceptual and logical thinking, ability to abstract information, and look at the bigger picture.
- Proven analysis skills with the ability to challenge designs / decisions.
- Proven experience in managing and resolving complex issues using analytical and problem-solving skills.
- Ability to quickly get up to speed with the current data landscape and apply acquired analysis and data skills to new contexts and approaches.
- Building relationships and networking, with high levels of motivation and collaboration.
- Excellent verbal and written communication skills with strong ability to communicate virtually through conference calls and video conferencing.
- Strong leadership skills and an ability to articulate, present and obtain approval for solutions at the right level for a wide audience (IT and Business).
- Strong planning, organization, and time management skills with a demonstrated ability to work to deadlines
- Commercial acumen and ability to apply this to Business and IT data requirements.
- A track record of consistently looking for ways to do things better and a good understanding of the mechanism necessary to successfully implement a change.
Good to have:
- Experience in data management and data lineage tools like Collibra, Alteryx and Solidatus
- Experience in Data Vault Modeling.
- Knowledge of Hadoop, Google Big Query is a plus.
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