Senior Data Engineer: Data Pipelines & Observability

Fuze Health Inc.; Columbia (SC); On-site; USD 140,000 - 175,000; Full time

Benefits offered by this job

Dental and vision plans

Medical plans and 401(k)

Group life insurance

HSA, FSA

Commuter benefits

Short-term and long-term disability

Paid holidays

Flexible vacation and sick time

Parental leave and caregiver leave

Lifestyle Spending Account

Job summary

Fuze Health is seeking a Senior Data Engineer to build and maintain a scalable data platform that delivers timely data for operations and business decisions. You will collaborate with Data Scientists, Data Analysts, and DevOps to codify infrastructure and enable scalable data processing.

The role focuses on deploying data pipelines, building observability metrics, and designing ELT/ETL workflows while handling large datasets across cloud environments. Strong SQL and Python skills are essential.

Qualifications

• Bachelor's Degree in a quantitative field (Statistics, Economics, Engineering, Mathematics, or Data Science)
• At least 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

• Deploy new data pipelines
• Design and build data observability platforms and metrics
• Build metadata driven pipeline solutions
• Monitor and optimize data transformations
• Build third party data integrations

Skills

SQL

Python

Cloud platforms

Infrastructure as Code

Data pipelines

ETL/ELT design

Snowflake

Education

Bachelor's degree

Master's degree

Tools

Terraform

Snowflake

AWS

GCP

Azure

Job description

Fuze Health is seeking a Senior Data Engineer to build and maintain a scalable data platform that delivers timely data for operations and business decisions. You will collaborate with Data Scientists, Data Analysts, and DevOps to codify infrastructure and enable scalable data processing.

The role focuses on deploying data pipelines, building observability metrics, and designing ELT/ETL workflows while handling large datasets across cloud environments. Strong SQL and Python skills are essential.