JPMorgan Data Quality Vice President 

United States, New York, New York 

513785581

The buy side gains a competitive advantage by using Fusion, as their data is seamlessly integrated and combined across multiple sources into a single data model. Leveraging this model allows for data-driven insights downstream to generate investment and operational alpha. Fusion is a cloud-native data solution built for institutional investors that delivers end-to-end data management, analytics and reporting.

As a Data Quality Lead within the Fusion team, you will be instrumental in advancing our data quality management capabilities. You will work closely with data product owners, technology teams, and program leads to ensure effective controls are in place across the data pipeline. Your role will be pivotal in ensuring our customers can access complete, accurate, and trusted data to generate insights and promote effective decision-making.

Job Responsibilities:

• Work with appropriate data product owners and help to define and document requirements for net new customers being onboarded to the Fusion platform and actively communicate risks, constraints, issues, and objectives.
• Work closely with data product owners with the analysis of data quality controls put in place and train AI models to adjust for data drift and change with requirements in BAU
• Work closely with program lead to continue to enhance approach (leveraging automatization and leading practices) for identifying and prioritizing key Data Quality challenges affecting data acquisition, transformation and data delivery and ensure that effective programs of work are in place to meet growing demands
• Work with Technology teams to continue to embed Data Quality capabilities across the entire data pipeline via an API based architecture for both soft and hard checks / controls
• Drive enhanced Customer User experience, work closely with Technology teams to continue to ensure Data Quality requirements are integrated with metadata, application architecture, and directly in the Fusion front-end
• Identify and manage risks/issues proactively; help to create solutions to address limitations while minimizing time to market and minimizing control/operational risk
• Help with the documentation and facilitation of training programs to upgrade the knowledge and capability of Operations staff in Data Quality assessment and improvement

Required qualifications, capabilities, and skills:

• 6+ years of financial services industry experience
• Strong Data Quality management background and exposure in other aspects of data governance including but not limited to data catalog, data discovery, data profiling, etc...
• Experience working with Data Quality management solutions – vendor or home grown
• Experience of data controls, testing methodologies and enhancing existing processes
• Experience with performing business analysis on data using SQL via tools like DBeaver
• Experience with additional development using Python, Java, etc.
• Experience in articulating detailed feature requirements
• User-centric design approach that involves rapid testing and iteration of designs
• Ability to execute an agenda, gain consensus and facilitate decision making across virtual and multi-functional, cross-regional teams
• A proven track record of strategic delivery, effectively resolving challenges to ensure timely delivery and achieve business benefits
• Analytical skills, problem solving, strong critical thinking and decision-making skills based upon fact and business/industry knowledge

Preferred qualifications, capabilities, and skills:

• Experience with Collibra Data Quality Platform (or Gartner defined leader) will be highly beneficial
• Domain knowledge in a securities services environment such as custody, fund accounting or middle office will be viewed favorably
• Domain knowledge of relevant reference data domains such as Instrument reference data, ESG, Indexes etc. will also be viewed favorably
• Thrives in a fast-paced, collaborative, team-oriented, cross-functional environment
• Has a strong analytical skills and experience with leveraging data quality tools to provide insights into data quality health.
• A strong data background is required with experience in data analysis, data quality monitoring, remediation, and issue management.
• Work with high degree of independence, be self-motivated and tenacious