Morgan Stanley
Department:
Investment Management - Private Alternatives
Job Summary:
The Senior Data Architect will play a pivotal role in shaping the data strategy for the Private Alternatives asset classes within the Investment Management division. This position focuses on constructing a robust, scalable data architecture that supports the extraction, processing, insight generation and utilization of data for business decision-making, reporting /visualization. The role involves close collaboration with various stakeholders to ensure that data products meet business needs with high quality and efficiency. Key Responsibilities:
Data Architecture Design: ◦ Develop and implement comprehensive data architecture strategies that support the needs of Private Alternatives including Real Assets and Private Credit & Equity (PC&E), etc. ◦ Design scalable data models that facilitate efficient data procurement, storage, processing, and analysis. Data Modeling: ◦ Create logical and physical data models that reflect business data consumption needs. ◦ Ensure data models support data mining, business intelligence, and analytics activities. ◦ Semantic models to facilitate managed self-service operations. Data Governance and Quality: ◦ Help establish and facilitate management of data definitions, standards, policies, and procedures. ◦ Enhance data quality by setting up frameworks for data consistency, accuracy, and completeness. ◦ Lead efforts in data cataloging for improved data discovery and understanding. Collaboration: ◦ Work closely with data engineers, analysts, product owners, and other stakeholders to deliver data products that align with business objectives. ◦ Facilitate cross-functional team efforts to ensure data architecture supports all aspects of the business. Tool Utilization and Expertise: ◦ Utilize advanced data modeling tools to design and optimize data architectures. ◦ Stay updated with the latest trends in data technology and methodologies applicable to asset management. ◦ Familiarity with business intelligence tool set ecosystem, and strong experience with some. Training and Mentorship: ◦ Provide guidance, training, and mentorship to junior data modelers and architects within the team. Project Leadership: ◦ Lead or contribute significantly to projects that involve large-scale data integration, migration, or transformation. Qualifications:
Educational Background:
Bachelor's or Master’s degree in Computer Science, Information Systems, or related field. Experience: ◦ Minimum of 7-10 years in a data architecture or data modeling role, preferably within the financial services or investment management sector. ◦ Proven experience with data warehousing solutions, ELT processes, and data integration techniques. Technical Skills: ◦ Expert level knowledge of SQL and experience with database management systems (e.g., PostgreSQL, Sybase, SQL Server, Snowflake, etc.). ◦ Proficiency in data modeling tools like ERwin, PowerDesigner, or equivalent tools. ◦ Familiarity with big data technologies and cloud services (AWS, Azure, Google Cloud). ◦ Familiarity with AI-enabled toolsets for data management and analytics is a plus. Domain Knowledge: ◦ Preferable understanding of asset management, particularly in Real Estate, Private Equity, or Credit sectors. Soft Skills: ◦ Exceptional analytical and problem-solving capabilities. ◦ Strong communication skills to articulate complex data concepts to non-technical stakeholders. ◦ Ability to work in a collaborative, agile environment.
#J-18808-Ljbffr
Investment Management - Private Alternatives
Job Summary:
The Senior Data Architect will play a pivotal role in shaping the data strategy for the Private Alternatives asset classes within the Investment Management division. This position focuses on constructing a robust, scalable data architecture that supports the extraction, processing, insight generation and utilization of data for business decision-making, reporting /visualization. The role involves close collaboration with various stakeholders to ensure that data products meet business needs with high quality and efficiency. Key Responsibilities:
Data Architecture Design: ◦ Develop and implement comprehensive data architecture strategies that support the needs of Private Alternatives including Real Assets and Private Credit & Equity (PC&E), etc. ◦ Design scalable data models that facilitate efficient data procurement, storage, processing, and analysis. Data Modeling: ◦ Create logical and physical data models that reflect business data consumption needs. ◦ Ensure data models support data mining, business intelligence, and analytics activities. ◦ Semantic models to facilitate managed self-service operations. Data Governance and Quality: ◦ Help establish and facilitate management of data definitions, standards, policies, and procedures. ◦ Enhance data quality by setting up frameworks for data consistency, accuracy, and completeness. ◦ Lead efforts in data cataloging for improved data discovery and understanding. Collaboration: ◦ Work closely with data engineers, analysts, product owners, and other stakeholders to deliver data products that align with business objectives. ◦ Facilitate cross-functional team efforts to ensure data architecture supports all aspects of the business. Tool Utilization and Expertise: ◦ Utilize advanced data modeling tools to design and optimize data architectures. ◦ Stay updated with the latest trends in data technology and methodologies applicable to asset management. ◦ Familiarity with business intelligence tool set ecosystem, and strong experience with some. Training and Mentorship: ◦ Provide guidance, training, and mentorship to junior data modelers and architects within the team. Project Leadership: ◦ Lead or contribute significantly to projects that involve large-scale data integration, migration, or transformation. Qualifications:
Educational Background:
Bachelor's or Master’s degree in Computer Science, Information Systems, or related field. Experience: ◦ Minimum of 7-10 years in a data architecture or data modeling role, preferably within the financial services or investment management sector. ◦ Proven experience with data warehousing solutions, ELT processes, and data integration techniques. Technical Skills: ◦ Expert level knowledge of SQL and experience with database management systems (e.g., PostgreSQL, Sybase, SQL Server, Snowflake, etc.). ◦ Proficiency in data modeling tools like ERwin, PowerDesigner, or equivalent tools. ◦ Familiarity with big data technologies and cloud services (AWS, Azure, Google Cloud). ◦ Familiarity with AI-enabled toolsets for data management and analytics is a plus. Domain Knowledge: ◦ Preferable understanding of asset management, particularly in Real Estate, Private Equity, or Credit sectors. Soft Skills: ◦ Exceptional analytical and problem-solving capabilities. ◦ Strong communication skills to articulate complex data concepts to non-technical stakeholders. ◦ Ability to work in a collaborative, agile environment.
#J-18808-Ljbffr