RIT Solutions, Inc.
Our client, a top tier Management & Strategy Consulting firm is looking for an experienced
Data Architect
to join a top tier Client. The ideal candidate will have a strong background in data architecture, with expertise in Snowflake, Erwin, fund accounting, and portfolio accounting. As a Data Architect, you will be responsible for designing, implementing, and optimizing data solutions that support financial data management, analytics, and reporting, ensuring high performance, scalability, and security.. Qualification & Responsibilities: • Design and implement scalable and efficient data architectures to support the company's financial data needs, leveraging Snowflake for cloud-based data solutions. •
Data Modelling : Use Erwin or similar tools to develop logical, physical, and conceptual data models for portfolio and fund accounting data. •
ETL Processes : Collaborate with data engineers to build and optimize ETL pipelines to process large datasets from various financial systems. •
Integration with Financial Systems : Ensure seamless integration of data between accounting systems, portfolio management systems, and data warehouse solutions. •
Data Governance : Establish data governance practices, including data quality, data security, and metadata management.
Data Architect
to join a top tier Client. The ideal candidate will have a strong background in data architecture, with expertise in Snowflake, Erwin, fund accounting, and portfolio accounting. As a Data Architect, you will be responsible for designing, implementing, and optimizing data solutions that support financial data management, analytics, and reporting, ensuring high performance, scalability, and security.. Qualification & Responsibilities: • Design and implement scalable and efficient data architectures to support the company's financial data needs, leveraging Snowflake for cloud-based data solutions. •
Data Modelling : Use Erwin or similar tools to develop logical, physical, and conceptual data models for portfolio and fund accounting data. •
ETL Processes : Collaborate with data engineers to build and optimize ETL pipelines to process large datasets from various financial systems. •
Integration with Financial Systems : Ensure seamless integration of data between accounting systems, portfolio management systems, and data warehouse solutions. •
Data Governance : Establish data governance practices, including data quality, data security, and metadata management.