Emoneyadvisor
Business Intelligence Analyst
datafull-timeRemote
SALARY
$80k – $100k/yr
WORK TYPE
remote
JOB TYPE
full-time
INDUSTRY
fintech
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About the role
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.
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