Objective

As a Data Modeler, you will develop, implement, and manage robust data models and systems that meet the specialized needs of a financial institution. Guided by the DAMA-DMBOK v2 framework, this role emphasizes data security, regulatory compliance, data quality, metadata management, master data management, and the continuous advancement of AI and machine learning solutions.

Key Responsibilities

1. Banking-Specific Data Modeling and Management

· Develop and maintain data models tailored to various banking domains (e.g., retail, transaction, investment banking, and risk management).

· Design high-performance data solutions capable of handling large volumes of financial transactions and customer data.

· Ensure alignment with relevant financial regulations (e.g., Basel, GDPR, PCI-DSS) and industry standards.

2. Data Governance and Compliance

· Implement and uphold data governance frameworks rooted in DAMA-DMBOK v2 principles.

· Oversee data accuracy, integrity, and adherence to financial industry standards and regulations.

· Formulate and enforce policies for data privacy, security, and ethical data usage.

· Establish and guide metadata management strategies consistent with the bank’s overall data strategy.

3. Leadership in Financial Data Management (Applicable for Lead Level Only)

· Direct and mentor teams of data modelers and data mappers specialized in financial systems.

· Champion the adoption of data warehousing, advanced analytics, and Business Intelligence (BI) solutions, including AI and Generative AI.

· Foster a data-driven culture by advocating for insights-based decision-making at all organizational levels.

4. Technology Integration and Innovation

· Work closely with IT Solutions Architecture and Enterprise Architecture teams to ensure alignment of data strategies with broader organizational goals.

· Take ownership of technology selection for data platforms and collaborate with technology teams to implement these solutions.

· Continually evaluate and integrate emerging technologies (AI, ML, Generative AI) into the data models, ensuring performance and compliance.

· Oversee cloud migration and evaluate cloud-based data management solutions (e.g., AWS, Azure, Snowflake, Databricks), ensuring they meet security and regulatory mandates.

· Lead the design of AI, ML, data science, and generative AI solutions to elevate the bank’s analytical and predictive capabilities.

· Stay current with new and upcoming trends in data practices, proactively recommending improvements and innovations.

5. Project Management and Collaboration

· Collaborate with IT, Risk Management, Finance, and other departments to align data modeling strategies with overarching business objectives.

· Lead and execute data modeling projects within budget and time constraints, adhering to industry and internal standards.

· Serve as the primary liaison to external stakeholders, including regulatory bodies and technology partners.

Qualifications

· Bachelor’s degree or higher in Computer Science, Information Technology, Finance, or related field.

· A minimum of 5 years’ experience in data modeling within the banking/financial services sector.

· Thorough understanding of financial regulations (e.g., Basel III, GDPR, PCI-DSS) affecting data management.

· Proven track record in banking data and technology environments.

Skills

· Deep expertise in financial databases, data modeling, and ETL processes specific to banking.

· Proficiency in data security and compliance technologies aligned with regulatory requirements.

· Familiarity with fintech innovations and their applications in data modeling.

· Strong strategic planning, communication, and stakeholder management skills.

· Experience with cloud services (AWS, Azure, Snowflake, Databricks) tailored for financial services.

· Professional certifications relevant to data management (e.g., CDMP) or financial services (e.g., FRM, CFA) are a plus.

Experience Levels

1. Data Modeler

· 3 to 8 years of relevant experience focusing on data warehousing and analytics in a financial setting.

· Solid understanding of risk management, financial reporting, and transaction processing systems.

2. Senior Data Modeler

· 5 to 8+ years of experience in designing and managing comprehensive data models within banking and finance.

· Demonstrated leadership in rolling out major data initiatives, as well as mentoring junior team members.

3. Lead Data Modeler

· 8+ years of experience directing Data Modeling teams in a financial services environment.

· Proven track record in executive-level communication, strategic planning, and driving enterprise-wide data initiatives.

· Strong managerial skills to lead cross-functional teams and shape organizational data strategies.

Note: This role requires a deep commitment to upholding data governance best practices and industry regulations. Candidates should possess a genuine passion for leveraging data to streamline financial processes, manage risk, and enhance customer experience while continuously exploring new trends and technologies in data practices.