Senior Manager, Data Analytics and Insights

Fidelity•Westlake, TX

About The Position

Partners with multiple product teams to support adoption of a modernized data platform, align end-to-end reporting requirements, and manage transition efforts. Creates comprehensive data lineages from source systems to target outputs, supports structured data modeling, and enables reliable, consumption-ready datasets. Analyzes, manipulates, and processes large datasets using advanced analytical techniques and tools, and provides advanced analytic solutions and data management services to stakeholders and senior leadership. Contributes to technical infrastructure capabilities for forecasting, big data analytics, and machine learning models. Develops data visualizations and analytic tools that illustrate performance trends and uncover drivers of success. Provides data-driven insights and expertise throughout the software development lifecycle to inform business processes and help create digital experiences for clients and associates. Defines and leads enterprise-level data strategy and analytics initiatives, develops analytical frameworks, addresses complex business challenges, supports reporting cycles, and advises senior leadership. The role also contributes to research and investment processes through non-traditional and unstructured data and data science applications, and mentors junior analysts. Fidelity states that it will not provide immigration sponsorship for this position. Its onsite working model is transitioning through a phased rollout; expectations vary by role and location and may evolve.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent), and five years of experience as a Senior Manager, Data Analytics and Insights or in a closely related occupation; alternatively, a master’s degree in one of these fields (or foreign education equivalent) and three years of such experience.
Experience performing data analysis, database structuring, and database operations using Power BI, Tableau, Python, and Snowflake in a brokerage and financial services environment.
Demonstrated expertise in data transformation for analytics, quality control, and self-service reporting in data warehouse architecture and ETL processes, including SQL queries and Common Table Expressions for query optimization and performance tuning.
Demonstrated expertise applying Power BI and Tableau visualization best practices for exploratory analysis, dashboard development, wireframing, rapid prototyping, and iterative solution design.
Demonstrated expertise analyzing brokerage and financial-domain data using SQL and Python, including transactions, assets, flows, redemptions, and product data.
Ability to write, maintain, and troubleshoot Python scripts and process large-scale financial data in relational databases using Snowflake.
Demonstrated expertise applying regression analysis, hypothesis testing, time-series analysis, and factor analysis to evaluate KPIs and financial data.
Ability to deliver actionable insights and strategic recommendations, support metadata and visualization initiatives, respond to oversight and risk requests, and assess organizational data consumption patterns.

Responsibilities

Partner with multiple product teams to support adoption of a modernized data platform and align end-to-end reporting requirements and transition efforts.
Create data lineages from source systems to target outputs, support structured data modeling, and enable reliable, consumption-ready datasets.
Analyze, manipulate, and process large datasets using advanced analytical techniques and tools.
Provide advanced analytic solutions and data management services to stakeholders and senior leadership.
Contribute to development of technical infrastructure for forecasting, big data analytics, and machine learning models.
Deliver data visualizations and analytic tools that illustrate performance trends and uncover key drivers of success.
Provide data-driven insights throughout the software development lifecycle to inform business processes and digital experiences.
Define and lead enterprise-level data strategy and analytics initiatives.
Develop and implement advanced analytical frameworks to support strategic data initiatives and address complex business challenges.
Support daily, weekly, and monthly production reporting cycles across analytic environments; ensure input data availability, successful processing, accurate statistical output, and proper report generation.
Perform independent and complex technical and functional analysis for multiple divisional initiatives.
Develop insights to support strategic business goals and respond to ad-hoc analysis requests from business stakeholders.
Contribute non-traditional and unstructured data and data science applications to enhance research and investment processes.
Advise senior leadership on data-driven decision-making.
Mentor junior analysts.