Senior Product Data Analyst - Stock Plan Services

Fidelity•Covington, KY

3d•Onsite

About The Position

The Product Data Analyst is a key member of the Stock Plan Services (SPS) Customer Solutions organization, responsible for partnering with Product Leaders, Stakeholders, Technology teams, Operations, and Compliance partners to define, analyze, and deliver business data solutions that support SPS products and services. This role serves to empower and inform decision makers by analyzing data as part of business and technology requirements. The ideal candidate can understand complex data ecosystems, interpret complex data sets, identify cross-program data dependencies and patterns, understand data as input and output, and drive process improvements across the organization. This role requires strong collaboration with cross-functional teams and a deep understanding of data platforms, modeling strategies, input/output data flows, and analyzing up and downstream consumption needs.

Requirements

6+ years of experience in business analysis, data analysis, or product ownership.
Experience with data recordkeeping platforms, reporting systems, and application designs.
Proficiency in data analytical tools (e.g. SQL, Excel, OBIEE, Power BI).
Deep understanding of data modeling and structuring.
Solid experience with data stores, data lakes, data warehouses, and cloud platforms (e.g., AWS, Snowflake).
Experience with data governance and security standards.
Ability to translate complex data and data requirements into meaningful stories to inform decision-making.
Ability to represent data requirements in the context of business priorities to multiple stakeholder profiles.

Nice To Haves

Bachelor’s degree preferred.
Superb communication, organizational, and time management skills.

Responsibilities

Engaging stakeholders, product managers, and technology leaders to understand the right problems from a data perspective.
Collaborate with business and technical teams to analyze and document current system behavior and define future state requirements.
Communicate findings and recommendations clearly through written, verbal, and visual formats.
Accept ambiguity and synthesize information from various sources to formulate actionable insights.
Analyze data movement as part of job flows to identify problem points, inefficiencies, dependencies, and inconsistencies.
Apply knowledge of dimensional, relational, and unstructured modeling strategies to support data architecture.
Continuous documentation of data lineage, tracing data flow from origination to consumption.
Recommend improvements based on data-driven insights and design-oriented modeling approaches.
Influence and motivate colleagues without formal authority, fostering a collaborative and knowledge-sharing environment.
Stay updated on industry trends and standards in reporting, data analysis, and process optimization.
Proactively suggest improvements to data consumption and output methods, technologies, and workflows to improve efficiency and accuracy.