Business Intelligence Analyst

eMoney Advisor is a company focused on helping people talk about money through their wealth management system. The Business Intelligence Analyst plays a key role in supporting data-informed decisions by transforming raw data into meaningful insights and managing analytics projects to solve complex problems.

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