Senior Data Architect - VP P5

Morgan Stanley; New York (NY); On-site; USD 90,000 - 160,000; Full time

Job summary

Join a forward-thinking company as a Senior Data Architect, where you will shape the data strategy for Private Alternatives. This role involves designing robust data architectures, collaborating with diverse teams, and ensuring high-quality data governance. You'll leverage your extensive experience in data modeling and architecture to drive impactful business decisions. The ideal candidate will possess strong technical skills in SQL and database management, along with the ability to communicate complex concepts effectively. If you're ready to make a significant impact in the investment management sector, this opportunity is perfect for you.

Qualifications

• 7-10 years of experience in data architecture or modeling, preferably in finance.
• Expertise in SQL and database management systems is crucial.

Responsibilities

• Design and implement data architecture strategies for Private Alternatives.
• Collaborate with stakeholders to ensure data products meet business needs.

Skills

Data Architecture

Data Modeling

SQL

Analytical Skills

Problem-Solving

Communication Skills

Education

Bachelor's degree in Computer Science

Master’s degree in Information Systems

Tools

ERwin

PowerDesigner

PostgreSQL

SQL Server

Snowflake

AWS

Azure

Google Cloud

Job description

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:

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. Training and Mentorship:
   ◦ Provide guidance, training, and mentorship to junior data modelers and architects within the team.
7. Project Leadership:
   ◦ Lead or contribute significantly to projects that involve large-scale data integration, migration, or transformation.

Qualifications:

1. Educational Background: Bachelor's or Master’s degree in Computer Science, Information Systems, or related field.
2. 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.
3. 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.
4. Domain Knowledge:
   ◦ Preferable understanding of asset management, particularly in Real Estate, Private Equity, or Credit sectors.
5. 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.