Personal Investing Business Intelligence Analyst

Manulife•Boston, MA

6h•Hybrid

About The Position

The Business Intelligence Analyst will support the delivery of analytics, reporting, and data solutions that enable informed business decision-making across Marketing, Product, Finance, and Strategy. This role sits at the intersection of business and data, helping translate complex datasets into meaningful insights and scalable reporting tools.

Requirements

1–3 years of experience in data analytics, business intelligence, or related field
Experience working with large datasets, data preparation, and analysis to derive business insights
Experience with data visualization tools (e.g., Power BI, Tableau)
Strong Excel skills and proficiency in Microsoft Office tools
Demonstrated ability to communicate effectively with both technical and non-technical stakeholders
Strong problem-solving skills and attention to detail

Nice To Haves

Experience in financial services, retirement, or investment management
Proficiency in SQL and/or Python for data analysis and data manipulation
Experience working in agile or SAFe delivery environments
Familiarity with semantic data modeling and modern data architectures
Experience in a global or matrixed organization

Responsibilities

Analyze business performance across financial results, customer behavior, and digital engagement to identify trends, risks, and opportunities
Synthesize complex data into clear, actionable insights to support strategic decision-making
Support business decision-making through timely exploratory and ad hoc analysis, clearly communicating findings to stakeholders
Design, build, and maintain dashboards and reports using modern visualization tools (e.g., Power BI)
Enhance existing reporting solutions with a focus on automation, scalability, and reducing manual processes
Ensure data outputs are accurate, consistent, and aligned with defined KPIs and business metrics
Develop and maintain scalable semantic data models to support enterprise analytics and reporting needs
Partner with data engineering teams to define requirements, test new data pipelines, and ensure data quality and availability
Support the ingestion and transformation of large datasets for analytical use
Gather and prioritize business requirements across cross-functional stakeholders, translating business needs into analytical solutions
Act as a key point of contact for reporting needs, managing priorities and aligning stakeholder expectations
Collaborate within an agile delivery model to support sprint planning, testing, and release cycles