Analytics Engineer, Unity
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Job Description
Analytics Engineer building dbt-powered data products for Rightway’s healthcare navigation and PBM platform. Transforming healthcare data into reliable models for reporting, insights, and AI-enabled analytics.
Responsibilities:
- Design, develop and maintain scalable analytics-ready data models, primarily in dbt, supporting PBM and care navigation operations
- Transform complex healthcare data into trusted datasets for operational reporting, client insights, financial analysis and strategic decision-making
- Translate pharmacy benefits and healthcare navigation workflows, business rules and operational processes into transparent, maintainable and auditable data models
- Partner with data and analytics engineers, data analysts and business stakeholders to deliver reliable reusable data products
- Optimize data models and warehouse performance for large-scale PBM and care navigation datasets
- Implement automated data quality checks, testing frameworks and reconciliation processes
- Establish documentation standards, data lineage and analytics engineering guardrails
- Contribute to version control, CI/CD, incremental models, code reviews and observability best practices
- Contribute to data governance and modeling standards
- Build data foundations for self-service analytics, AI-assisted insight generation and future agentic analytics engineering use cases
- Monitor emerging technologies and identify opportunities to incorporate AI into analytics engineering workflows
Requirements:
- 3+ years of experience in analytics engineering, data modeling, data warehousing or a related field
- Strong experience with dbt (core or cloud) and modern analytics engineering best practices (required)
- Advanced SQL proficiency
- Experience developing data transformations and workflows using Python
- Strong understanding of dimensional modeling, medallion architecture, semantic modeling and scalable data architecture principles
- Experience building and maintaining production-grade data models, data quality tests, and documentation
- Experience with cloud data warehouses such as Amazon Redshift, Snowflake, or BigQuery
- Experience orchestrating and monitoring data pipelines using tools such as Apache Airflow or Dagster
- Experience working within cloud environments, preferably AWS
- Familiarity with Git, CI/CD, pull request reviews, testing, and deployment workflows
- Interest or experience in AI-enabled development workflows and analytics tooling, including Claude, Claude Skills, Model Context Protocol (MCP), and AI-assisted engineering practices
- Strong problem-solving and analytical skills
- Effective communication skills and ability to collaborate with technical and non-technical stakeholders
Benefits:
- Bonus
- Equity
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