We are seeking a Data Management Analyst to join GMO's Data Management team within the Technology organization. This role supports the quality, governance, integration, and lifecycle management of data used across GMO's investment and business platforms, including security master, portfolio, reference, market, and other enterprise data. This position provides broad exposure to GMO's data ecosystem and offers opportunities to contribute to platform enhancements, data quality initiatives, workflow automation, and the ongoing modernization of data management practices.
The analyst will work with Operations, Trading, Investments, Compliance, Client Service, and Data Engineering teams, focusing on data quality enhancement and continual process improvement through improvement of existing data quality frameworks and automation of hands-on data workflows and report monitoring. The ideal candidate will have experience working with financial or enterprise data, strong analytical and problem-solving skills, and experience using technology to improve data quality, controls, and operational efficiency.
The position is based in Boston and offers a hybrid work model. This person will be required to be in the office a minimum of 2 days per week, working the remainder of the week either in the office or remotely (to be discussed with the candidate).
Develop a deep understanding of GMO's data architecture, data flows, business processes, internal platforms, databases, and vendor applications supporting security, portfolio, reference, market, and enterprise data.
Design and maintain automated data onboarding, validation, and enrichment processes across GMO's Enterprise Data Warehouse, internal systems, and third-party platforms including BlackRock Aladdin, NeoXam DataHub, and Eagle PACE.
Build and enhance monitoring, alerting, and control frameworks that proactively identify data quality issues, operational exceptions, and processing failures.
Analyze data across multiple systems and databases to identify root causes, recurring issues, control gaps, and opportunities for process re-engineering and automation.
Partner with Operations, Investment, Compliance, Client Service, and Data Engineering teams to understand data requirements and deliver scalable solutions to business problems.
Translate business and operational requirements into technical specifications for data pipelines, system enhancements, controls, workflow automation, and data quality frameworks.
Develop and maintain solutions using Python, SQL, APIs, and data platforms to automate data validation, reconciliation, exception management, reporting, and operational workflows.
Support the design, testing, and implementation of data integrations, platform enhancements, vendor connectivity, and system modernization initiatives.
Establish and maintain data governance standards including data definitions, lineage, ownership, quality rules, exception thresholds, controls, and metadata management.
Create and maintain technical documentation, support models, control procedures, data dictionaries, and operational runbooks to improve transparency and supportability.
Continuously identify and implement opportunities to reduce manual effort, improve scalability, strengthen controls, and increase the reliability and resilience of data management processes.
Support platform modernization, cloud adoption, data migrations, and conversion initiatives through data mapping, testing, automation, validation, and issue resolution.
Evaluate, prototype, and implement automation, artificial intelligence, and advanced analytics capabilities to improve data operations, monitoring, data quality, and user productivity.
Contribute to the development of reusable frameworks, tools, and services that enable standardized data management practices and reduce operational dependency on manual processes.
Bachelor's degree or equivalent relevant experience.
3-7 years of experience in asset management, financial services, investment operations, data management, reference data, security master, portfolio data, market data, or investment technology.
Experience using Python or similar tools for data analysis, validation, or automation.
Working knowledge of relational databases and experience using Python and SQL for data analysis and issue investigation.
Experience working with financial, operational, or enterprise data across multiple systems.
Experience with investment data platforms such as NeoXam DataHub, BlackRock Aladdin, and Eagle PACE.
Familiarity with financial market data providers such as Bloomberg, LSEG, or ICE.
Strong analytical and problem-solving skills, with the ability to investigate data issues and communicate findings clearly.
Strong attention to detail and a consistent focus on data quality, controls, and operational reliability.
Ability to document processes and requirements and collaborate effectively with business and technology stakeholders.
Strong organizational, written communication, and time-management skills.
Conscientious, self-directed, and collaborative, with intellectual curiosity and a strong work ethic.
Flexibility to participate in rotational after-hours support as needed.
GMO is committed to the recruitment, employment, and promotion of all candidates equally, regardless of an individual's gender, race, color, national origin, ancestry, age, religion, pregnancy, marital status, sexual orientation, gender identity or expression, military or veteran status, genetic information, physical or mental disability (except where such disability is a bona fide occupational disqualification) or any other classification protected under federal, state or local law.
GMO will not offer visa sponsorship for this opportunity.
