Senior Data Engineer — Remote/Hybrid, Pipelines & MLOps

Coderio; New Jersey; Hybrid; USD 140,000 - 180,000; Full time

Job summary

Coderio seeks a Senior Data Engineer based in the US to design, build, and maintain robust data pipelines across our cloud platform. You will enable data products through batch and stream processing, optimize architecture, and collaborate with Data Scientists and ML Engineers to automate workflows in production.

You will work with a tech stack including Python, PySpark, SQL, AWS and GCP services, Docker, and Terraform, while driving data quality and governance across raw and curated datasets.

Qualifications

• 5+ years of experience in data engineering, designing and running large-scale data systems.
• Strong Python and advanced SQL with a focus on performance tuning.
• Hands-on experience with AWS or GCP data services and modern data platforms.
• Experience building batch and streaming ETL/ELT pipelines and data modeling.
• Familiarity with MLOps, DevOps practices, and CI/CD pipelines.
• Excellent written and spoken English communications.

Responsibilities

• Design, build, and deploy scalable data pipelines for batch and streaming data.
• Develop and optimize ETL/ELT processes using Python, PySpark, and SQL.
• Collaborate with ML/DS teams to support models and retraining data needs.
• Monitor performance, troubleshoot issues, and optimize cloud resources.
• Implement data quality controls and governance across data lakes and warehouses.
• Maintain CI/CD pipelines and document architectural standards.

Skills

Python

SQL

Batch & streaming data processing

Data modeling

Tools

AWS Redshift

AWS Glue

AWS EMR

AWS MWAA

AWS S3

GCP BigQuery

Docker

Terraform

Git

CI/CD pipelines

UNIX/Linux

Job description

Coderio seeks a Senior Data Engineer based in the US to design, build, and maintain robust data pipelines across our cloud platform. You will enable data products through batch and stream processing, optimize architecture, and collaborate with Data Scientists and ML Engineers to automate workflows in production.

You will work with a tech stack including Python, PySpark, SQL, AWS and GCP services, Docker, and Terraform, while driving data quality and governance across raw and curated datasets.