Job description

• Data Modeler in a data warehouse environment, preferably in the banking or financial services industry.
• Strong knowledge of data modelling concepts, techniques, and best practices (e.g., dimensional modelling, normalization).
• Proficiency in data modelling tools such as ERwin, Power Designer, or similar tools.
• Solid understanding of data warehousing concepts, ETL processes, and data integration methodologies.
• Experience with SQL and database technologies (e.g., Oracle, SQL Server, Snowflake) for data modelling and analysis.
• Familiarity with data governance principles, data quality management, and metadata management.
• Excellent analytical and problem-solving skills with the ability to translate business requirements into effective data models.
• Strong communication skills to collaborate with cross-functional teams and present complex concepts to both technical and non-technical stakeholders.
• Proficiency with Source Control: BitBucket/GIT, Subversion (SVN), Perforce, or similar.
• Must possess good leadership skills and have ability to lead a team of 3-5 developers.

Responsibilities

• Collaborate with business stakeholders, data architects, and developers to understand data requirements and translate them into effective data models.
• Design and develop conceptual, logical, and physical data models for the data warehouse environment.
• Analyze and evaluate existing data structures to identify opportunities for improvement and optimization.
• Ensure that the data models adhere to industry best practices, standards, and guidelines.
• Work closely with the development team to implement and validate data models in the data warehouse.
• Perform data profiling and analysis to identify data quality issues and recommend data cleansing and remediation strategies.
• Collaborate with data governance teams to ensure compliance with regulatory requirements and data governance policies.
• Document data models, data dictionaries, and related metadata for effective data management and understanding.
• Participate in data modeling reviews and provide guidance to junior team members.