Analytics (BI) Engineer

Role overview

An Analytics/BI Engineer position that sits at the intersection of business intelligence and data engineering. The role centers on building and maintaining reporting assets across multiple BI suites while shaping the underlying data models that power them. Success depends on proactive collaboration with cross-functional stakeholders, clear communication, and a disciplined approach to data quality and documentation.

Responsibilities

- Develop, modify, and maintain dashboards and reports in BI tools, keeping metric definitions consistent and queries well-tuned for performance. - Translate business requests received through ticketing workflows into accurate, actionable data visualizations. - Create and maintain database views, derived tables, and other analytical objects that support ongoing reporting needs. - Perform data modeling and transformation work on large datasets to enable reliable downstream reporting. - Investigate and resolve data discrepancies, validating accuracy across source systems and reports. - Document the logic, assumptions, and definitions behind key metrics and dashboards, and contribute to improvements in data structure and warehouse organization.

Requirements

- Four or more years of experience in analytics, BI, or data engineering roles. - Advanced SQL proficiency, including joins, CTEs, aggregations, and window functions. - Hands-on experience working with a cloud-based data warehouse. - Practical experience building reports in BI platforms such as Power BI, Tableau, or Looker. - Ability to interpret business requirements and translate them into technical solutions. - Strong attention to detail with disciplined data validation habits. - Bachelor's degree in computer science, engineering, or a closely related field.

Nice to have

- A leadership orientation: defining reporting standards, documenting KPIs, optimizing large data models, and supporting junior teammates. - Experience with dashboard engineering that emphasizes storytelling and usability.

Benefits and work setup

- Engagement on work that combines modern data engineering and AI-adjacent practices. - Opportunities for ongoing professional development and career advancement. - A collaborative team culture that emphasizes knowledge sharing and cross-functional partnership. - An equal opportunity employer with a stated commitment to inclusive, unbiased hiring.