Business Intelligence Analyst

Job Description

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.

RESPONSIBILITES

• 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.

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