Lead Analytics Engineer – Data Modeling, Quality

This is a fully remote position, open to applicants in United States.

📋 Description

• Take the initiative to triage and resolve issues related to pipeline data quality.

• Create at least one new dbt model or enhance an existing one to align with current modeling standards.

• Develop a dbt test suite for models that currently lack coverage.

• Comprehend the complete pipeline from data ingress through silver and gold layers, and trace data quality issues back to their root source.

• Cultivate strong professional relationships with clients and cross-functional teams, including Data Engineering and Customer Success.

• Have an in-depth understanding of Arcadia's entire data stack, from data ingress through silver and gold layers to downstream consumers.

• Lead at least one improvement project, whether it is technical (such as model refactoring or a new data quality framework) or process-oriented (for example, developing a promotion playbook or triage workflow).

• Be recognized as a leader within the department, with peers and stakeholders seeking your expertise in data modeling and quality.

• Operate autonomously across the full scope of responsibilities with minimal oversight.

• Successfully complete and implement two or more improvement projects that have measurable effects on data quality or operational efficiency.

⛳️ Requirements

• Possess a Bachelor's or Master's degree in Computer Science, Statistics, Business, Economics, or a related discipline.

• Proficient in advanced SQL, including window functions, complex CTEs, aggregation patterns, and performance tuning on columnar databases.

• Hands-on experience with dbt, including authoring models, tests, macros, and yml documentation, along with familiarity with incremental strategies.

• Have healthcare data literacy, including knowledge of claims data (professional, institutional, pharmacy), clinical data (EHR entities), and common quality dimensions (such as member months, coverage rates, and null patterns).

• Maintain a data quality mindset, capable of distinguishing between source data issues and transformation issues, designing systematic validation checks, and clearly communicating data quality insights.

• Exhibit clear communication skills, able to convey technical findings to clients and non-technical stakeholders.

• Demonstrate strong analytical judgment, with the ability to assess distributions and identify anomalies.

• Manage multiple projects concurrently, utilizing AI tools for organization and efficiency.

• Show a genuine eagerness to learn about and apply AI tools to enhance operational efficiency.

🏝️ Benefits

• Collaborate with a talented team on some of the most challenging and fulfilling issues in healthcare data.

• Enjoy a flexible, fully remote work environment with the resources and support necessary to excel in your role.

• Gain exposure to senior leadership.

• Be at the forefront of AI adoption—utilize cutting-edge tools to enhance your work and influence the team's operations in an AI-first setting.

• Contribute to meaningful improvements in healthcare data operations by enhancing the quality, reliability, and trustworthiness of data that influences patient care decisions.

• Join a mission-driven organization that is reshaping the healthcare industry.

• Become part of the dynamic, energized, diverse, and purpose-driven Arcadian Community.