Data Engineer (Health Data Metrics)

Socket.dev; Durham (NC); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Competitive salary and benefits

Growth opportunities

Collaborative culture

Impact on healthcare

Professional development

Job summary

Socket.dev is seeking a mid to senior Data Engineer to design and optimize healthcare data infrastructure. You will build scalable ETL/ELT pipelines on AWS, work with SQL, Python, and dbt, and contribute to data models aligned with FHIR and HEDIS standards.

You will collaborate with stakeholders to integrate population health analytics and ensure HIPAA-compliant data handling while leveraging tools like Redshift Serverless and Temporal for reliability and scalability.

Qualifications

• US-based candidates only.
• Proven experience in data engineering roles with SQL, Python, and AWS data infrastructure.
• Experience with dbt and Spark/PySpark for transformation and modeling.
• Familiarity with healthcare data systems, including HEDIS, population health, and FHIR data models.

Responsibilities

• Design, build, and maintain scalable data pipelines for ETL/ELT on AWS.
• Develop, test, and deploy robust SQL/Python data solutions.
• Implement and manage data warehousing using Redshift Serverless and AWS services.
• Utilize dbt for data modeling, transformation, and documentation.
• Use Temporal for pipeline orchestration and automation.

Skills

SQL

Python

AWS

HEDIS metrics

FHIR data models

Data warehousing

Workflow orchestration

dbt

Spark/PySpark

Tools

dbt

Spark/PySpark

Temporal

Airflow

Dagster

Terraform

Redshift Serverless

Job description

About the role

We are seeking a skilled and motivated mid level to senior level Data Engineer to join our team and play a critical role in building and optimizing the data infrastructure that powers our healthcare AI solutions. The ideal candidate will bring expertise in modern data engineering tools and techniques, with a specific focus on healthcare quality metrics, population health, and data interoperability standards such as FHIR. Level and salary will commensurate with experience.

Key Responsibilities

Data Engineering and Development

• Design, build, and maintain scalable, efficient data pipelines for ETL/EL T processes on AWS.
• Develop, test, and deploy robust solutions using SQL and Python for data transformation and analysis.
• Implement and manage data warehousing solutions using Redshift Serverless and other AWS data services.
• Leverage dbt (Data Build Tool) for data modeling, transformation, and documentation.
• Utilize workflow orchestration tools such as Temporal for pipeline automation.

Healthcare Data Expertise

• Work with healthcare quality metrics such for value-based care and ensure data alignment with industry standards.
• Collaborate with stakeholders to integrate population health tools and analytics into data workflows.
• Develop and maintain familiarity with FHIR data models and healthcare interoperability standards for seamless integration of healthcare data sources.
• Ensure compliance with HIPAA and other healthcare regulatory requirements in all data handling processes.

Optimization and Innovation

• Identify and resolve performance bottlenecks in data pipelines, ensuring high availability and reliability.
• Optimize data storage and querying performance within Redshift Serverless and AWS infrastructure.
• Stay current with emerging trends in data engineering and healthcare technology, incorporating innovations into the data ecosystem.

Collaboration and Impact

• Partner with data and engineering teams to ensure data is accessible and meets business requirements.
• Develop scalable solutions for integrating complex healthcare datasets, ensuring data quality and accuracy.
• Contribute to the design and implementation of secure, scalable, and efficient data architecture on AWS.

Required Qualifications

• Must be US based. No foreign applicants will be considered.
• Proven experience in data engineering roles with expertise in SQL, Python, and AWS cloud-based data infrastructure.
• Experience with tools like dbt and Spark/PySpark for data transformation and modeling.
• Familiarity with healthcare data systems, including HEDIS metrics, population health tools, and FHIR data models.
• Knowledge of data warehousing and workflow orchestration tools.

Preferred Skills

• Strong understanding of healthcare data standards, including FHIR, HL7 and CQL.
• Hands-on experience with data modeling, normalization, and schema design for complex datasets.
• Experience designing and building scalable, production-grade data pipelines using orchestration tools such as Airflow, Dagster, or Temporal.
• Hands-on experience with AWS data and compute services, including Glue, EMR, Iceberg, Redshift Serverless, S3, Lambda, and related technologies.
• Strong experience with data transformation and distributed processing, using tools such as dbt, Spark/PySpark, and Pandas.
• Experience designing and operating HIPAA-compliant data architectures and handling sensitive healthcare data.
• Demonstrated ability to optimize data pipelines for performance, scalability, and reliability in cloud environments.
• Strong problem-solving skills and attention to detail when working with large, complex, and heterogeneous datasets.
• Experience with Infrastructure as Code (IaC) tools such as Terraform.

What We Offer

• Competitive salary and benefits package.
• Opportunity to work in a fast-paced, innovative environment.
• Professional growth and development opportunities.
• Collaborative and supportive team culture.
• Chance to make a meaningful impact on the healthcare industry.