Lead Analytics Engineer – Data Modeling, Quality

🕒 May 28

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Arcadia

201 - 500 employees

💰 $29.5M Venture Round on 2020-01

Arcadia is dedicated to happier, healthier days for all. We transform diverse data into a unified fabric for health. Our platform delivers actionable insights for our customers to advance care and research, drive strategic growth, and achieve financial success. For more information, visit arcadia.io.

📋 Description

• Independently triage and resolve pipeline data quality issues • Author at least one new dbt model or refactor an existing one to meet current modeling standards • Design a dbt test suite for a set of models lacking coverage • Understand the end-to-end pipeline from ingress through silver and gold, and be able to trace a data quality issue to its root layer • Building strong working relationships with clients and cross-functional partners (Data Engineering, Customer Success) • Deeply familiar with Arcadia's full data stack — from ingress through silver, gold, and downstream consumers • Driving at least one improvement project forward, whether technical (e.g. model refactor, new DQ framework) or process-focused (e.g. promotion playbook, triage workflow) • Recognized as a leader within the department — peers and stakeholders seek out your expertise on data modeling and quality • Operating independently across the full scope of the role with minimal guidance • Two or more improvement projects completed and in production, with measurable impact on data quality or operational efficiency

🎯 Requirements

• Bachelor's or Master's degree in Computer Science, Statistics, Business, Economics, or a related field • Advanced SQL: window functions, complex CTEs, aggregation patterns, performance tuning on columnar databases • dbt: hands-on experience authoring models, tests, macros, and yml documentation; familiarity with incremental strategies • Healthcare data literacy: working knowledge of claims data (professional, institutional, pharmacy), clinical data (EHR entities), and common quality dimensions (member months, coverage rates, null patterns) • Data quality mindset: ability to differentiate source data issues from transform issues, design systematic validation checks, and communicate data quality findings clearly • Clear communicator — able to translate technical findings for clients and non-technical stakeholders • Strong analytical judgment — you can look at a distribution and know when something is wrong • Ability to manage several projects simultaneously, leveraging AI tooling to stay organized and efficient • Genuine desire to learn and apply AI tools for operational efficiency

🏖️ Benefits

• Work alongside a talented team on some of the most complex and rewarding challenges in healthcare data • Flexible, fully remote work environment with the resources and support to do your best work • Exposure to senior leaders • Be on the front lines of AI adoption — use cutting-edge tools to accelerate your work and shape how the team operates in an AI-first environment • Make a meaningful impact on healthcare data operations by improving the quality, reliability, and trustworthiness of data that drives patient care decisions • Be a part of a mission driven company that is transforming the healthcare industry • Become a member of the talented, energized, diverse and purpose-driven Arcadian Community

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