Dimensional's Investment Engineering department is responsible for ownership of investment data, which means managing data from acquisition through distribution, driving analysis to create information from data, and creating the information and analysis consumed by internal and external reports. Investment Engineering is a hub group touching numerous areas of the implementation of the investment process and interacting with most other departments within Dimensional. 

The Data Solutions team's primary responsibilities involve overseeing the incoming base-level data and the centralized management and distribution of investment data to Dimensional’s internal Portfolio Management, Trading, and Reporting systems. 

The Data Solutions team seeks an Analyst/Associate capable of supporting key initiatives underpinning our daily implementation process. This role will work within the team to analyze the quality of investment data within Dimensional, including security reference, prices, ratings, and all other data crucial to the investment process. They will be a subject matter expert in the team’s existing data products and work to design new products. Success in this role will mean delivering clean, accurate data to internal as well as external clients in a timely manner, being creative at finding different ways to analyze and present relevant investment data and enhancing operational efficiencies at Dimensional to deliver value-added investment solutions to our clients.  

Responsibilities:  

• Support Dimensional's investment processes by ensuring tools and systems are built with appropriate business logic.  

• Compile, cleanse, and manage large data sets from multiple sources to support investment systems.  

• Research and evaluate vendor data to assess quality and recommend optimal consumption patterns.  

• Conduct data analysis using SQL Server, Snowflake, and other structured/ unstructured database technologies.  

• Partner with Portfolio Management, Trading, Compliance to address portfolio construction questions and perform related analysis.   

• Collaborate with internal clients to gather and define requirements for core business systems, and then design, build, and test data pipelines in partnership with data engineer resources.  

• Assist in shaping data architecture for internal distribution of investment data, including defining and building data structures for end-user consumption.  

• Drive efficiency through automation, process design, and implementation.  

• Mentor and provide guidance to junior analysts, fostering skill development and knowledge-sharing across the team.    

Qualifications:  

• Bachelor's degree in Finance, Accounting, Computer Science, Engineering, Business, or a related field. Master’s degree and/or professional certifications (e.g. CFA) preferred.  

• 3-5+ years of experience working with large investment datasets, performing quantitative analysis, and leveraging SQL, Python, or similar data management tools.  

• Strongly preferred: experience working with financial data sets and vendor platforms (Bloomberg, Factset, Refinitiv, Morningstar, etc.).  

• Demonstrated interest and passion for financial markets. 

• Experience working in Agile/Scrum teams, writing business requirements, and communicating effectively with software engineers. 

• Self-starter with proven ability to manage multiple projects and meet deadlines. 

• Strong analytical and quantitative problem-solving skills. 

• Attention to detail with the ability to connect findings to broader objectives and goals.  

• Excellent communication skills with the ability to convey complex ideas and bridge investment professionals and engineering teams. 

This role is not eligible for immigration sponsorship.