Analytics Engineer

Overview

Founded by some of the nation’s top orthodontists and headquartered in Grand Rapids, MI, Orthodontic Partners (OP) is a fast-growing national orthodontic service organization that provides partner doctors with a full range of administrative, marketing, HR, and financial support services. Our mission is to build a better orthodontic partnership model by bringing together leading business and clinical minds and sharing insights that inspire our partners, teams and patients.

We’ve grown to support over 30 top orthodontic practices across nearly 70 locations and 15 states and are just getting started. We’re looking for highly motivated individuals to join us as we revolutionize the orthodontics industry by making orthodontic care more convenient, affordable, faster and easier for patients.

The Analytics Engineer serves as a bridge between data engineering and analytics by building and improving data pipelines, analytical datasets, and reporting-ready data models. This role is designed for an early-career professional who wants to grow at the intersection of data engineering and analytics, with a strong emphasis on SQL-driven data transformation, pipeline reliability, and analytics-ready data modeling.

The position works closely with the Data Engineer, BI Developer, and BI Manager to ingest new data sources, transform and structure data for reporting and analytics, and improve the reliability, performance, and documentation of the analytics platform. Over time, this role is expected to grow into increased ownership of production datasets, data quality monitoring, and pipeline optimization, and semantic modeling.

• Write and maintain SQL transformations used to clean, standardize, and model data for reporting, analytics, and self-service use cases.
• Assist in managing database objects such as tables, views, schemas, and transformations used by reporting and analytics tools.
• Help build and maintain structured data layers (e.g., raw, cleaned, and reporting layers).
• Work with the Data Engineer to onboard new data sources using a modern analytics stack.
• Create and maintain curated datasets and reporting tables consumed by Power BI and other internal tools.
• Perform data validation and reconciliation to ensure accuracy and reliability.
• Assist in developing data quality checks, monitoring, and alerting.
• Troubleshoot data issues and support root cause analysis.
• Document data pipelines, transformations, business logic, and data lineage.
• Contribute to experimentation and adoption of AI-driven tools or models to enhance analytics, data preparation, and insight generation.

• Foundational SQL skills for querying, transforming, and validating data.
• Basic understanding of data modeling concepts for reporting and analytics.
• Enthusiasm and ability to learn cloud-based data platforms and modern analytics tools.
• Strong attention to detail and commitment to data accuracy.
• Analytical mindset with the ability to ask good questions and investigate data issues.
• Clear communication skills and comfort working with both technical and non-technical stakeholders.

• 1–3 years of relevant experience in data analytics, business intelligence, data engineering, or a related role.
• Bachelor’s Degree or equivalent experience in computer science, information systems, engineering, mathematics, business, or a related field.
• Experience working with SQL and relational databases.
• Exposure to reporting or analytics tools such as Power BI, Tableau, or similar platforms.

• Exposure to ETL/ELT concepts or analytics transformation frameworks.
• Familiarity with cloud-based data platforms (Azure preferred).
• Experience with data ingestion or orchestration tools.
• Interest in data quality, automation, and scalable analytics.
• Curiosity about AI or advanced analytics techniques.

• Gain a working understanding of existing data pipelines, data sources, and reporting datasets.
• Document key data pipelines, transformations, and data lineage.
• Support recurring data processes independently with guidance.
• Build or enhance at least one production analytics dataset.
• Implement basic…