Senior Data Engineer - Remote US, Build Scalable Pipelines

Coderio; Oregon; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote-first culture

Flexible work options

Career growth opportunities

Job summary

Coderio is seeking a Senior Data Engineer based in the United States to design, build, and maintain robust data pipelines and scalable infrastructure across our cloud platform. You will enable Data Products and collaborate with Data Scientists to deploy resilient data pipelines in production.

Work location is US-based with remote or hybrid options; authorization to work in the US is required. The role emphasizes data quality, governance, and MLOps practices across AWS/GCP environments.

Qualifications

• 5+ years of experience in data engineering with large-scale pipelines.
• Proficiency in Python and SQL with PySpark.
• Hands-on experience with AWS or GCP data services.
• Experience with batch and streaming data processing and data warehousing.
• Strong communication and collaboration with cross-functional teams.

Responsibilities

• Design, build, and maintain scalable data pipelines for batch and streaming data.
• Develop and optimize ETL/ELT processes using Python, PySpark, and SQL.
• Collaborate with ML and data science teams to support model lifecycles.
• Monitor performance, troubleshoot issues, and optimize resource usage.
• Ensure data quality, governance, and documentation across data lakes and warehouses.
• Contribute to MLOps practices and CI/CD pipelines.

Skills

Python

SQL

PySpark

Data Modeling

Data Warehousing

ETL/ELT Pipelines

Batch & Stream Processing

MLOps

CI/CD

Unix/Linux

Tools

Docker

Terraform

Git

CI/CD Pipelines

BigQuery

Redshift

MWAA

Job description

Coderio is seeking a Senior Data Engineer based in the United States to design, build, and maintain robust data pipelines and scalable infrastructure across our cloud platform. You will enable Data Products and collaborate with Data Scientists to deploy resilient data pipelines in production.

Work location is US-based with remote or hybrid options; authorization to work in the US is required. The role emphasizes data quality, governance, and MLOps practices across AWS/GCP environments.