Senior Analytics Engineer - Business Intelligence

Role overview Own the governed data models, pipelines, and reporting layer that help teams across a business make consistent, well-informed decisions. This hands-on senior role combines analytics engineering and business intelligence: it turns source data and stakeholder questions into trusted metrics, reusable models, and useful dashboards, while setting technical standards and mentoring colleagues.

Responsibilities - Design and maintain shared data models, tables, views, and semantic layers so key measures are defined consistently across reports. - Build and operate ETL/ELT pipelines, with checks and validation that keep data accurate, timely, and dependable. - Work with data producers and business partners to translate decision needs into durable models and pipelines rather than isolated dashboard logic. - Define business KPIs using SQL and Python, and document their meaning and use. - Develop dashboards and visualizations with tools such as Tableau or Power BI, supporting leadership and operational reporting. - Improve data platform architecture, advise on secure and scalable data access, and mentor teammates through reviews, pairing, documentation, and shared practices.

Requirements - A bachelor’s degree in a relevant field plus 6 or more years of experience, or a master’s degree plus 3 or more years. - Strong practical experience in data modeling and warehouse design, including reusable models used by multiple reports or tools. - Strong SQL skills and proficiency in Python for data transformation, pipeline work, or analysis. - Production experience building and maintaining ETL/ELT pipelines with data quality checks and validation. - Experience with at least one BI platform and enough dashboard-building knowledge to collaborate effectively with analysts. - Experience mentoring or guiding engineers or analysts, and communicating technical decisions to technical and nontechnical audiences. - Comfort working through ambiguous requirements, collaborating with business stakeholders, and balancing priorities in an Agile environment.

Nice to have Experience with cloud data platforms such as Databricks or Snowflake, AWS services, dbt or comparable tested modeling practices, and relational, NoSQL, vector, or lakehouse architectures. Background in ML/AI data workloads, semantic layers for natural-language BI, or automotive, robotics, or other safety-critical data is also useful. Familiarity with AI-assisted coding tools is expected, along with the judgment to review and validate their output.

Benefits and work setup The hiring hub is Ann Arbor, Michigan, and remote candidates across the United States may be considered. The listed US pay range is $160,800–$193,000.