eMoney Advisor, LLC (“eMoney”) provides technology solutions and services that help people talk about money. Rooted in comprehensive financial planning, eMoney’s solutions strengthen client relationships, streamline business operations, enhance business development and drive overall growth. More than 138,000 financial professionals across firms of all sizes use the eMoney platform to serve more than 7 million households throughout the U.S.

Job Summary

The Business Intelligence Analyst plays a key role in supporting data-informed decisions across eMoney by transforming raw data into meaningful insights. This role goes beyond foundational analysis by independently managing analytics projects, developing dashboards, implementing business logic, and partnering closely with business units to solve complex problems. The Business Intelligence Analyst defines KPIs, contributes to data governance, and ensures data integrity across systems. This role translates business questions into analytical solutions and supports the advancement of eMoney’s enterprise data ecosystem.

Job Responsibilities:

Own medium-complexity analytics projects from requirements gathering through delivery, working with stakeholders to define objectives and success metrics.

Analyze and interpret structured and unstructured data from multiple sources to uncover trends, patterns, and opportunities.

Design and develop reports and dashboards using BI tools (e.g., Power BI, Looker), aligning outputs with stakeholder needs and business goals.

Translate business logic into technical specifications and implement calculations, KPIs, and rules in analytics environments.

Conduct exploratory analysis and hypothesis testing to validate assumptions and guide business decisions.

Collaborate with data engineers and developers to ensure data flows, structures, and integrations meet analytical requirements.

Contribute to data governance efforts by creating, maintaining, and enforcing data definitions, metadata, and lineage documentation.

Apply data quality and validation techniques to improve trust in data across the organization.

Partner with operational and cross-functional teams to identify opportunities to optimize processes, improve client experience, and increase revenue.

Utilize basic data modeling techniques (e.g., star/snowflake schema) and assist in the development of data pipelines and ETL workflows.

Present findings to diverse audiences, using visual storytelling and plain-language explanations to drive alignment and action.

Requirements:

Bachelor’s degree in a quantitative discipline – math, statistics, data and analytics preferred or equivalent experience

3+ years’ experience in data science, statistical analysis, business intelligence or related consultative role

Skills:

Proficient in SQL, with experience writing and optimizing complex queries in a business environment.

Working knowledge of data modeling concepts (e.g., star schema, snowflake, normalization).

Familiarity with data pipeline/ETL processes and collaboration with data engineering teams.

Hands-on experience with data visualization and reporting tools (e.g., Power BI, Looker, Tableau).

Exposure to Python or other scripting languages for analysis or automation is a plus.

Strong analytical thinking and problem-solving abilities, with attention to detail and data accuracy.

Ability to clearly communicate findings and translate technical insights into business recommendations for both technical and non-technical audiences.

Experience contributing to data governance, including data quality practices, definitions, and metadata maintenance.

Comfortable managing priorities and working independently within fast-paced, collaborative environments.

Strong attention to detail

Strong analytical and problem-solving skills to interpret data and draw meaningful conclusions.