Data Modeler Jobs

Data Modeler

Apex Systems is a global IT services provider and our staffing practice has an opening for a Data Modeler professional who is proficient in building data models front to back and has designed it within ERwin tool to be placed at our client, a Big Five Bank.

We have placed multiple people on this very team and have personally qualified the requirement with the hiring manager.

• Location: Hybrid, 1-2 days in office per week.
• Client: Big Five Bank, Enterprise Data Management Office
• Terms: 6-month Contract to Hire. Must convert full-time.

Purpose

Seeking a skilled and experienced Financial Services Data Modeler to join our team. The successful candidate will be responsible for designing, implementing and maintaining complex data models for financial services applications, in order to support business operations, analysis and decision-making. This role will require a deep understanding of financial services data and systems, as well as strong analytical, communication and collaboration skills.

Must Haves:

• Excellent analytical and problem-solving skills, with the ability to identify and resolve complex data modeling issues and challenges.
• Good understanding of data management concepts and practices, such as data quality, metadata management, data lineage, data integration, data governance, etc.
• Strong proficiency in data modeling techniques and tools, such as ERwin, Purview, PowerDesigner, etc.
• 5+ years of experience in financial services data modeling, with deep knowledge of financial services data domains, such as banking, insurance, investments, risk management, compliance, etc.

Collaborate with business stakeholders, data analysts, developers and architects to understand business requirements, data sources and data flows, and design data models that meet business needs and technical standards.

Develop and maintain conceptual, logical and physical data models for financial services applications, ensuring data accuracy, completeness, consistency and integrity.

Create and maintain data dictionaries, data lineage, metadata and other documentation related to data models and data management processes.

Perform data profiling, data quality analysis and data cleansing activities to ensure data accuracy and completeness, and identify data issues and trends.