Remote Senior Data Engineer — Scalable Data Pipelines & Cloud

Humana Inc; Salem (OR); Remote; USD 118,000 - 162,000; Full time

Job summary

Humana Inc. is seeking a Senior Data Engineer to design, build, and maintain data processing architectures that convert structured and unstructured data into enterprise-scale insights.

The role centers on scalable pipelines, data models, governance, and collaboration with stakeholders across analytics and engineering teams. Responsibilities include data quality, modernization of data platforms in cloud environments, and mentoring peers to drive engineering excellence while ensuring reliability

Qualifications

• Bachelor's degree in a technical field such as CS/IS/Engineering.
• 5+ years in Data Engineering.
• Advanced SQL for data modeling and large-scale processing.
• Python for data engineering, automation, and pipelines.
• Experience with enterprise ETL/ELT solutions.
• Cloud-based data platforms knowledge.
• CI/CD, source control, and automated testing.
• Strong communication with technical and business stakeholders.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
• Build and optimize data models, curated datasets, and data products.
• Translate requirements into technical solutions with stakeholders.
• Establish and promote data quality, testing, monitoring, governance.
• Troubleshoot production data issues ensuring reliability and performance.
• Contribute to data platform modernization including cloud architectures.
• Participate in code reviews, design discussions, and architecture planning.
• Mentor and support other engineers toward engineering excellence.

Skills

SQL

Python

ETL/ELT design

Data modeling

Cloud data platforms

CI/CD & testing

Stakeholder communication

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or related field

Tools

Databricks

Snowflake

dbt

Job description

Humana Inc. is seeking a Senior Data Engineer to design, build, and maintain data processing architectures that convert structured and unstructured data into enterprise-scale insights.

The role centers on scalable pipelines, data models, governance, and collaboration with stakeholders across analytics and engineering teams. Responsibilities include data quality, modernization of data platforms in cloud environments, and mentoring peers to drive engineering excellence while ensuring reliability