Lead Data Analyst

Job Description:

As a Data Analyst/Data Modelling Specialist, you will be responsible for analyzing and modelling data to support our wealth management initiatives. You will work closely with cross-functional teams to understand business requirements, perform source-to-target transformations, and design data models that meet the needs of the organization. The ideal candidate will have a strong background in data analysis, data modelling, and financial services, with a focus on wealth management.

Responsibilities:

• Collaborate with business stakeholders to gather and analyze requirements for data analysis and modeling projects.
• Perform source-to-target transformations to ensure data quality, consistency, and integrity throughout the data lifecycle.
• Design and develop conceptual, logical, and physical data models that align with business objectives and regulatory requirements in wealth management.
• Utilize industry-standard data modeling techniques and tools to document and communicate data structures, relationships, and definitions.
• Work closely with technical teams to implement data models in relational databases, data warehouses, and other data storage solutions.
• Conduct data profiling and analysis to identify trends, patterns, and insights that drive decision-making in wealth management.
• Develop and maintain data dictionaries, metadata repositories, and other documentation to support data governance and compliance efforts.
• Collaborate with data engineers, data scientists, and other stakeholders to optimize data pipelines and workflows for performance and scalability.
• Stay current with industry trends, best practices, and emerging technologies in data analysis, data modeling, and financial services.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Finance, or related field.
• 7 to 10 years of experience in data analysis, data modeling, and data management, preferably in the financial services industry with a focus on wealth management.
• Strong understanding of source-to-target transformations, ETL processes, and data integration techniques.
• Proficiency in data modeling tools such as Erwin, Erwin Data Modeler, or similar tools.
• Hands-on experience with SQL, relational databases (e.g., SQL Server, Oracle), and data warehousing concepts.
• Knowledge of industry-standard data modeling methodologies (e.g., ER/Studio, Kimball Dimensional Modeling) and best practices.
• Excellent analytical, problem-solving, and communication skills, with the ability to translate complex business requirements into technical solutions.
• Experience working in Agile environments and collaborating with cross-functional teams.
• Certifications in data modeling or related areas (e.g., CDMP, DAMA) are a plus.