Sr. Data Engineer

Harnham; United States; On-site; USD 110,000 - 165,000; Full time

Job summary

Harnham is expanding its data capabilities with a greenfield healthcare data platform. The team designs and builds a modern data architecture, pipelines, and infrastructure to support enterprise-wide decision-making, analytics, and AI adoption.

You will own AWS-based pipelines, data modeling, and scalable infrastructure to integrate clinical, payer, and operational data. Ideal candidates bring 5+ years in data engineering, deep AWS, Airflow, Snowflake, and dbt expertise, and a track record of

Qualifications

• 5+ years of Data Engineering experience.
• Deep expertise in AWS data warehousing, AWS data pipelines, Airflow, Python, and SQL.
• Hands-on experience with Snowflake and dbt in modern cloud data environments, including building, transforming, and optimizing data models to support analytics and reporting workloads.

Responsibilities

• Design, build, and optimize AWS-based data pipelines and data warehouse solutions
• Develop and manage data orchestration workflows using Apache Airflow
• Build scalable data infrastructure supporting analytics, reporting, and business intelligence initiatives
• Establish and maintain AWS development environments and engineering best practices
• Integrate data from multiple internal and external sources, including APIs and enterprise platforms
• Partner with business and technical stakeholders to define data architecture standards
• Support the implementation of a new enterprise data platform in a greenfield environment
• Identify opportunities for automation, performance optimization, and scalability

Skills

Data engineering experience

Tools

AWS data warehousing

AWS data pipelines

Airflow

Python

SQL

Snowflake

dbt

Job description

Join a rapidly growing healthcare organization that is investing heavily in its data and technology capabilities. This team is building a modern data platform from the ground up, bringing together information from clinical systems, healthcare providers, payers, labs, and operational applications to support analytics, automation, reporting, and business growth.

This is a true greenfield environment where you'll play a key role in designing and building the data architecture, pipelines, and infrastructure that support enterprise-wide decision-making. The organization is focused on innovation, operational visibility, AI adoption, and scalable data solutions.

Responsibilities

• Design, build, and optimize AWS-based data pipelines and data warehouse solutions
• Develop and manage data orchestration workflows using Apache Airflow
• Build scalable data infrastructure supporting analytics, reporting, and business intelligence initiatives
• Establish and maintain AWS development environments and engineering best practices
• Integrate data from multiple internal and external sources, including APIs and enterprise platforms
• Partner with business and technical stakeholders to define data architecture standards
• Support the implementation of a new enterprise data platform in a greenfield environment
• Identify opportunities for automation, performance optimization, and scalability

Must Have Qualifications

• 5+ years of Data Engineering experience
• Deep expertise in AWS data warehousing, AWS data pipelines, Airflow, Python, and SQL
• Hands-on experience with Snowflake and dbt in modern cloud data environments, including building, transforming, and optimizing data models to support analytics and reporting workloads.

Preferred Qualifications

• Healthcare or healthcare analytics experience
• Experience working within greenfield data platform implementations