Analytics Engineer, Unity

rightwayhealthcare; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

rightwayhealthcare is seeking an analytics engineer to build and maintain data products that support pharmacy benefit and care navigation operations. You will translate complex workflows into reusable datasets for reporting, financial analysis, operational decisions, and self-service BI.

You will design scalable models with dbt, collaborate across data, analytics, clinical, product, and client teams, and help establish AI-assisted analytics foundations while ensuring quality and observability.

Qualifications

• 3+ years in analytics engineering, data modeling, or related areas.
• Strong dbt experience and modern analytics engineering practices.
• Advanced SQL skills with Python for transformations.
• Understanding of dimensional and semantic modeling, medallion architecture.
• Experience building production data models, quality tests, and documentation.
• Familiarity with cloud data warehouses, pipelines, Git, CI/CD, testing, and deployment.
• Strong analytical problem-solving and communication with technical and non-technical partners.

Responsibilities

• Develop and maintain scalable analytics models, primarily with dbt, for reporting, performance measurement, and operational analysis.
• Convert healthcare and pharmacy benefit rules and processes into transparent, auditable data transformations.
• Partner with data, analytics, clinical, product, client-facing, and operations teams to deliver reusable data products.
• Improve warehouse performance and support growing datasets and analytical needs.
• Create automated data quality checks, tests, reconciliations, documentation, and lineage.
• Apply engineering practices such as version control, incremental processing, code review, CI/CD, and observability; identify opportunities for AI-assisted analytics workflows.

Skills

Analytics engineering

Advanced SQL

Python

Data modeling

Data warehousing

CI/CD

Code review

Communication

Problem solving

Git

Tools

dbt

Airflow

Dagster

Git

Cloud data warehouses

Job description

Role overview

Build and maintain trusted data products that support pharmacy benefit and care navigation operations. This analytics engineering role translates complex healthcare workflows into reusable, well-documented datasets for reporting, financial analysis, operational decisions, and self-service business intelligence. It also helps establish the foundations for more automated and AI-supported analytics.

Responsibilities

• Develop and maintain scalable analytics models, primarily with dbt, for reporting, performance measurement, and operational analysis.
• Convert healthcare and pharmacy benefit rules and processes into transparent, auditable data transformations.
• Partner with data, analytics, clinical, product, client-facing, and operations teams to deliver reusable data products.
• Improve warehouse performance and support growing datasets and analytical needs.
• Create automated data quality checks, tests, reconciliations, documentation, and lineage.
• Apply engineering practices such as version control, incremental processing, code review, CI/CD, and observability; identify opportunities for AI-assisted analytics workflows.

Requirements

• Three or more years in analytics engineering, data modeling, data warehousing, or a related area.
• Strong dbt experience and knowledge of modern analytics engineering practices.
• Advanced SQL skills and experience using Python for transformations or data workflows.
• Understanding of dimensional and semantic modeling, medallion architecture, and scalable data design.
• Experience building production data models, quality tests, and technical documentation.
• Familiarity with cloud data warehouses, pipeline orchestration, cloud environments, Git, CI/CD, code review, testing, and deployment.
• Strong analytical problem-solving and communication skills when working with technical and non-technical partners.

Nice to have

• Experience with AWS, Redshift, Snowflake, BigQuery, Airflow, or Dagster.
• Interest in AI-assisted engineering and analytics tools, including willingness to learn emerging approaches.