Senior Data Engineer - Data Platform & Pipelines (Remote)

Fuze Health Inc.; Williamstown (NJ); Presencial; USD 140.000 - 175.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Dental, vision, and medical plans

401(k) retirement savings plan

life insurance

AD&D insurance

FSA/HSA

Descripción de la vacante

Fuze Health Inc. is seeking a Senior Data Engineer to build and maintain a platform delivering timely, accurate data for operations and decision-making. You will collaborate with Data Scientists, Data Analysts, and DevOps to codify infrastructure as code and ensure scalable data services.

The role focuses on deploying data pipelines, building observability, and integrating third-party data sources, with a strong emphasis on SQL and Python for large datasets.

Formación

• 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 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.

Responsabilidades

• Deploy new data pipelines and build data observability platforms and metrics.
• Design and build data pipelines and third party data integrations.
• Monitor and optimize data transformations and ELT/ETL workflows.

Conocimientos

SQL

Python

Data pipelines

ETL/ELT design

Cloud platforms

Infrastructure as code

Data observability

Educación

Bachelor's Degree (quantitative)

Master's Degree (quantitative)

Herramientas

Terraform

Snowflake

ETL tooling

Python

AWS

Descripción del empleo

Fuze Health Inc. is seeking a Senior Data Engineer to build and maintain a platform delivering timely, accurate data for operations and decision-making. You will collaborate with Data Scientists, Data Analysts, and DevOps to codify infrastructure as code and ensure scalable data services.

The role focuses on deploying data pipelines, building observability, and integrating third-party data sources, with a strong emphasis on SQL and Python for large datasets.