Senior Manager, Advanced Data Analytics and Insights

Fidelity Investments•Smithfield, RI

About The Position

We are seeking a Senior Manager, Advanced Data Analytics who is a data-driven professional and is passionate about transforming complex data into clear, trusted insights and scalable BI products. This role blends analytical and technical expertise with business acumen. As a full‑stack analytics professional, you’ll deliver end‑to‑end BI solutions and Insights while partnering with stakeholders to drive measurable outcomes.

Requirements

Bachelor’s or equivalent Degree with 4+ years of experience working with data insight solutioning.
Knowledge in business statistics and quantitative methods
Proficiency in SQL and Python (pandas, data processing libraries)
Experience with BI and analytical tools (e.g. Power BI, Tableau, and related tooling)
Expertise in data modeling, semantic layer design, and metric modeling
Experience with pipeline logic and ETL practices
Practice in strong data quality and reconciliation methods
Experience with cloud data warehouses and analytics platforms (e.g., Snowflake)
Experience with Stakeholder partnership, consultative communication, and data storytelling

Nice To Haves

BS/MS in Engineering, Computer Science, Data

Responsibilities

Translate business questions into clear analytical requirements, and create reporting experiences and insights that support decision‑making.
Own end-to-end delivery of production BI solutions.
Act as a consultative partner translating objectives into measurable outcomes while driving a consistent “single source of truth” across stakeholders and domains.
Perform deep data discovery of source‑to‑target relationships, data lineage, business rules, and operational nuances.
Optimize advanced SQL for large-scale data processing.
Build scalable, high-quality datasets through strong data shaping practices.
Document definitions, assumptions, and limitations to ensure auditability.
Partner with governance and platform teams to align on standards.
Design and maintain robust data quality controls—including validation, anomaly detection, and completeness checks to drive trust in data.
Design and deliver intuitive, high-performing dashboards and semantic reporting layers to enable self-service analytics aligned to business workflows.
Apply visualization best practices, optimize performance, and manage release lifecycles.
Apply statistical and quantitative methods for diagnostic and predictive insights (e.g., hypothesis testing, statistical comparisons).
Independently conduct advanced analyses and build business cases ROI/ impact measurement tied to actions and outcomes.