Senior Data Engineer - HealthTech Data Platform

Fuze Health Inc.

Santa Fe (NM)

Remote

USD 130,000 - 190,000

Full time

5 days ago
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Benefits offered by this job

Dental, vision, and multiple group med
401(k) retirement plan
Group life insurance
AD&D insurance
FSA/HSA
Commuter benefits
STD and LTD insurance
Supplemental insurance plans
Flexible vacation time
Paid sick time
Paid holidays and parental leave

Job summary

Fuze Health Inc. is seeking a Senior Data Engineer to build and maintain platforms delivering timely, accurate data to operational teams and business stakeholders.

You will collaborate with Data Scientists, Data Analysts, and DevOps to transform data into actionable insights and codify infrastructure as code. Responsibilities include deploying data pipelines, constructing observability dashboards, and enabling scalable ELT/ETL workflows using Python and cloud services.

Qualifications

  • Bachelor's Degree in a quantitative field such as Statistics, Economics, Engineering, Mathematics, or Data Science.
  • At least 4 years of work experience in software engineering.
  • Experience with AWS, GCP, or Azure.
  • Experience with AWS and Terraform.
  • Programming experience in Python.

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

Data analysis
Python programming
SQL data manipulation
Communication

Education

Bachelor's Degree in a quantitative field
Master's Degree in a quantitative field

Tools

AWS
GCP
Azure
Terraform

Job description

Fuze Health Inc. is seeking a Senior Data Engineer to build and maintain platforms delivering timely, accurate data to operational teams and business stakeholders.

You will collaborate with Data Scientists, Data Analysts, and DevOps to transform data into actionable insights and codify infrastructure as code. Responsibilities include deploying data pipelines, constructing observability dashboards, and enabling scalable ELT/ETL workflows using Python and cloud services.

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