Remote Senior Data Engineer – Data Platform & Pipelines

Fuze Health Inc.; Little Rock (AR); On-site; USD 140,000 - 175,000; Full time

Benefits offered by this job

Dental, vision and group medical plans

401(k) retirement savings plan

Life insurance & AD&D

Job summary

Fuze Health is seeking a Senior Data Engineer to design and maintain the data platform that fuels operational decisions and business insights. You will collaborate with data scientists, analysts, and DevOps to transform data into meaningful results and scale data pipelines.

Responsibilities include building observability platforms, metadata-driven workflows, and third-party data integrations while monitoring data transformations to ensure accuracy and performance.

Qualifications

• Bachelor's degree in a quantitative field such as Statistics, Economics, Engineering, Mathematics, or Data Science.
• 4+ years of work experience in software engineering.
• Experience with one or more of the major cloud vendors: AWS, GCP, Azure.
• Experience with infrastructure as code tools and methodologies.
• Experienced in SQL-based and python data manipulation with large datasets.

Responsibilities

• Build and maintain the data platform powering operations and business insights.
• Collaborate with Data Scientists, Data Analysts, and DevOps to scale data pipelines and infrastructure.
• Design data observability platforms and metrics to monitor quality and performance.
• Build metadata-driven pipeline solutions and third-party data integrations.
• Monitor and optimize data transformations across the data stack.

Skills

Python

SQL

Data manipulation

ELT/ETL

Education

Bachelor's degree in quantitative field

Master's degree (preferred)

Tools

AWS

Terraform

Snowflake

Job description

Fuze Health is seeking a Senior Data Engineer to design and maintain the data platform that fuels operational decisions and business insights. You will collaborate with data scientists, analysts, and DevOps to transform data into meaningful results and scale data pipelines.

Responsibilities include building observability platforms, metadata-driven workflows, and third-party data integrations while monitoring data transformations to ensure accuracy and performance.