Senior Manager, Data Analytics and Insights

Fidelity Investments•Westlake, TX

17h

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, supporting structured data modeling and 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 enhancements for forecasting, big data analytics, and machine learning models. Delivers data visualizations and analytic tools that show performance trends and reveal key drivers of success. Informs business processes with data-driven insights and expertise throughout the software development lifecycle to help create digital experiences for clients and associates. Fidelity will not provide immigration sponsorship for this position. The role is subject to Fidelity's onsite working model, which is being phased in across regions and roles; current onsite requirements 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 in the stated role or a closely related occupation; alternatively, a master's degree in one of these fields (or foreign education equivalent) and three years of experience.
Experience performing data analysis, database structuring, and database operations using Power BI, Tableau, Python, and Snowflake in a brokerage and financial services environment.
Expertise in data transformation for analytics, quality control, and self-service reporting in data warehouse architecture and ETL processes.
Experience writing SQL queries and using Common Table Expressions (CTEs) for query optimization and performance tuning.
Expertise applying data visualization best practices in Power BI and Tableau for exploratory analysis, dashboard development, wireframing, rapid prototyping, and iterative solution design.
Expertise using SQL and Python for analysis in brokerage and financial domains, 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.
Expertise applying regression analysis, hypothesis testing, time-series analysis, and factor analysis to evaluate KPIs and financial data.
Experience delivering actionable insights and strategic recommendations, supporting metadata and visualization initiatives, responding to oversight and risk requests, and assessing organizational data consumption patterns.

Responsibilities

Define and lead enterprise-level data strategy and analytics initiatives.
Develop and implement advanced analytical frameworks.
Support strategic data initiatives and address complex business challenges.
Assist with daily, weekly, and monthly production reporting across analytic environments.
Ensure required input data is available, processes run successfully, statistical output is accurate, and reports are generated properly.
Perform independent, complex technical and functional analysis for multiple divisional initiatives.
Develop innovative insights to support strategic business goals.
Respond to ad hoc data analysis requests from business stakeholders supporting their projects.
Contribute to incorporating 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.
Partner with product teams on adoption of a modernized data platform, reporting requirements, and transition efforts.
Create data lineages and support structured data modeling and reliable, consumption-ready datasets.
Contribute to technical infrastructure capabilities for forecasting, big data analytics, and machine learning models.
Deliver visualizations and analytical tools that illustrate performance trends and identify key success drivers.