Data Quality Engineer

2 days ago

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Crossover Health

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Healthcare Insurance • Wellness

Crossover Health is a healthcare company focused on innovative primary care services. They offer both virtual and in-person healthcare solutions through their health centers, delivering a comprehensive range of services including primary care, physical medicine, mental health coaching, and occupational medicine. Crossover Health partners with employers and brokers to provide integrated healthcare plans that aim to reduce healthcare costs and improve patient outcomes. Since 2010, they have been pioneering an advanced primary care model in the United States, emphasizing a holistic approach to healthcare through their licensed care teams across all 50 states.

1001 - 5000 employees

Founded 2010

⚕️ Healthcare Insurance

🧘 Wellness

📋 Description

• Own the QA strategy for data pipelines, ensuring accuracy, completeness, and reliability of healthcare and operational data. • Maintain comprehensive documentation of data models, lineage, and critical fields in core tools like Snowflake, dbt, and Tableau. • Map data lineage from source systems (e.g., EMR, eligibility, claims) through modeling and reporting, ensuring visibility across the entire data lifecycle. • Design and implement data quality tests using dbt tests, Elementary, or similar QA tools. • Expand automated data QA test coverage across systems with limited or no existing validation. • Identify and validate data integrity issues across key sources such as claims, EMR, client files, and internal systems, assess impact, and coordinate resolution with cross-functional teams. • Maintain an issue tracker and regularly report on open items and progress to stakeholders. • Act as a liaison across Data Engineering, Data Science and Analytics, Product, Security, and Operations to support and advocate for data quality. • Support root cause analysis by debugging test coverage or validation scripts. • Partner with Data Engineering to recommend improvements to data models and pipelines based on QA findings. • Support the onboarding of new data sources by defining QA and documentation requirements in partnership with data engineering. • Performs other duties as assigned.

🎯 Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Science, or related field • 4+ years of experience in a data quality, data engineering, analytics engineering, or data governance role • Strong knowledge of QA methodologies and data testing frameworks (e.g., dbt tests, Elementary, Great Expectations) • Proficiency in: SQL and dbt (including documentation, testing, and modeling) • Python for scripting, QA automation, or monitoring workflows • Data pipelines orchestration tools (e.g., Airflow, Fivetran) • Snowflake • Proficiency in writing clear, concise, and comprehensive test plans, test cases, and documentation • Ability to identify and resolve data issues across complex systems with minimal supervision • Excellent problem-solving skills and attention to detail. • Strong communication and teamwork skills. • Ability to work independently and manage multiple priorities in a fast-paced environment.

🏖️ Benefits

• Medical Insurance • Dental Insurance • Vision Insurance • Short- and Long-Term Disability • Life Insurance • Paid Time Off • 401K