Brief Description

The Analytics Engineer is a key contributor to our data and analytics ecosystem, bridging data engineering, business intelligence, and analytics. This role owns the full data lifecycle—from ingesting and transforming data to building dashboards, administering BI platforms, and enabling business users through training and data literacy.

Qualifications

Bachelor’s degree in computer science, data science, information systems, or a related field; or equivalent professional experience.
3–5 years of experience in analytics engineering, data engineering, BI development, or a closely related role.
Demonstrated experience building and maintaining data pipelines, models, and BI solutions in production environments.
Experience working cross-functionally with business teams to translate requirements into data products.
Proficiency in SQL for data modeling, transformations, and performance optimization.
Proficiency in Python for automation, data manipulation, and analytics workflows.
Experience working with APIs for data ingestion, integration, and automation.
Familiarity with medallion/lakehouse architectures and developing transformation pipelines (bronze ? silver ? gold).
Strong skills in BI and data visualization tools (e.g., Power BI, Tableau, Domo, Looker, or equivalent).
Experience with version control (e.g., Git) and modern data development practices.
Experience administering BI platforms, including governance, permissions, and content management.
Knowledge of data governance, metadata management, and data quality practices.
Ability to communicate technical concepts clearly to non-technical audiences.
Experience training and enabling business users in data literacy, visualization techniques, and self-service analytics.
Strong problem-solving skills and comfort taking ownership across the full data lifecycle.
Excellent communication and collaboration skills.
Ability to develop and execute complex research projects with minimal supervision.
Punctual, have a good work attitude, and work cooperatively with others in the department and company.
Accept and benefit from constructive criticism.
Any other equivalent combination of training and experience.

Typical Duties And Responsibilities

Partner with business stakeholders to understand requirements and deliver actionable data products.
Design, build, and maintain BI dashboards and visualizations that support decision-making.
Train and support business users in data literacy, visualization best practices, and self-service analytics.
Administer and govern the BI platform, including permissions, content management, and standards.
Build and manage data pipelines and transformations across a medallion architecture.
Apply business logic, validation, and documentation to ensure accuracy, consistency, and trusted datasets.
Monitor and troubleshoot data quality and pipeline issues, implementing automation where possible.
Contribute to internal documentation, playbooks, and knowledge-sharing to strengthen team practices.
Stay current on tools and methods, recommending improvements to platforms, processes, and governance.

EOE/Vet/Disabled

Summary

Onsite medical clinic for employee, spouse and family members, 18 and under, living at home; Medical, Dental, 401k, Life Insurance, Short and Long Term Disability, paid vacation/holidays) plus some not so usual (free security system, free UPS shipping), so you don't have to worry about self or family.

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Analytics Engineer