Data Engineer 2

Remote (United States)

Job Details

Location: United States

Workplace: Remote

Employment Type: Full-Time

Experience: 5+ years of SQL experience and 5+ years of healthcare data analysis experience

Core Areas: Data Pipelines, ETL Processes, SQL, Python, Data Modeling, Database Management, Healthcare Claims Data, Data Visualization

Compensation: $90,397-$108,477 annually

About the Role

The Data Engineer 2 is responsible for designing, developing, and maintaining data pipelines, ETL workflows, databases, and data models that support healthcare data processing and analytics. This position focuses on transforming complex datasets into accurate, reliable, and accessible information while improving data quality, storage efficiency, and analytical capabilities. Key responsibilities include data integration, database development, data transformation, and maintaining the integrity of data throughout its lifecycle.

The role combines hands-on data engineering with healthcare claims data analysis, reporting, and visualization. Working with health policy experts, data analysts, and healthcare stakeholders, the position uses SQL, Python, R, and analytical technologies to address complex data challenges. The work requires substantial knowledge of multi-payer databases, public healthcare programs, claims processing, and healthcare utilization, cost, quality, and equity.

What You'll Do

• Design, develop, and maintain data pipelines, ETL processes, and workflows that extract, clean, transform, and prepare data from multiple sources for analysis and reporting.
• Maintain data integrity, quality, consistency, and accuracy throughout the data processing lifecycle.
• Design, develop, and maintain databases, data models, and schemas to support efficient data storage, organization, and retrieval.
• Analyze healthcare claims data and related datasets to identify patterns, trends, and actionable insights concerning healthcare quality, affordability, utilization, and equity.
• Develop reports, dashboards, and data visualizations that communicate complex analytical findings to nontechnical stakeholders.
• Collaborate with health policy experts, analysts, healthcare stakeholders, and other cross-functional teams to understand business requirements and translate them into practical data solutions.
• Apply data profiling, manipulation, transformation, and analytical techniques to prepare complex datasets for reliable interpretation.
• Identify opportunities to enhance data infrastructure, streamline processing workflows, improve data quality, and strengthen analytics capabilities.
• Stay informed about emerging technologies, industry developments, and best practices in data engineering, data analysis, and visualization.

Qualifications

Required Experience

• At least 5 years of hands-on experience working with SQL.
• At least 5 years of experience as a data analyst in the healthcare industry.

Required Skills

• Deep knowledge of healthcare data, multi-payer databases, public healthcare payers, claims processing, and healthcare claims data analytics.
• Strong understanding of U.S. healthcare policy, healthcare trends, and factors affecting eligibility, utilization, cost, and equity.
• Knowledge of the role of state governments in healthcare.
• Expertise in data analysis and visualization using SQL, Python, R, Excel, or comparable technologies.
• Proficiency in data profiling, manipulation, cleaning, and transformation using Pandas, SQL, or similar tools.
• Advanced proficiency in data visualization platforms such as Tableau or Power BI.
• Familiarity with data modeling, database management, and cloud-based data solutions, including AWS, Microsoft Azure, or Google Cloud.
• Solid understanding of statistical analysis, data mining, and machine learning concepts.
• Strong analytical reasoning, problem-solving, and critical-thinking abilities, with careful attention to data accuracy and detail.
• Excellent communication and collaboration skills, including the ability to explain complex data findings clearly and concisely to technical and nontechnical audiences.

Preferred Qualifications

• Bachelor's or master's degree in healthcare administration, data science, statistics, or equivalent work experience.
• Healthcare data analysis experience specifically involving claims data.