Senior Data Engineer - Remote/Hybrid US, Data Pipelines

Coderio; New York (NY); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote-first

Job summary

Coderio in the United States is seeking a Senior Data Engineer to design, build, and maintain robust data pipelines and scalable infrastructure across our cloud platform. In this role, you will play a key part in enabling Data Products throughout their lifecycle—sourcing data via batch and stream processing, optimizing data architecture, and ensuring data quality.

Collaborate with Data Scientists and ML Engineers to automate workflows, implement MLOps practices, and monitor pipeline performance.

Qualifications

• 5+ years of experience in Data Engineering or related field.
• Mastery of Python and advanced SQL (query optimization).
• Hands-on experience with cloud data platforms (AWS/GCP) and modern data processing (PySpark).
• Proficiency with UNIX environments, Docker, Git, and CI/CD pipelines.
• Solid understanding of data structures, batch/stream processing, and ML lifecycle familiarity.
• Excellent verbal and written English communication skills.

Responsibilities

• Design, build, and deploy scalable data pipelines for batch and streaming data ingestion into data lakes and warehouses.
• Develop and optimize ETL/ELT processes using Python, PySpark, and SQL.
• Collaborate with Data Scientists and ML Engineers to automate MLOps workflows and gather model interaction data.
• Monitor, troubleshoot, and optimize pipeline performance and storage utilization across cloud platforms.
• Implement data quality frameworks and governance across raw and curated datasets.
• Apply DevOps standards, document architectures, and maintain CI/CD pipelines.

Skills

Python

PySpark

SQL

Data Modeling

Data Warehousing

ETL/ELT

Batch Processing

Streaming

MLOps

English Communication

Tools

Docker

Terraform

CI/CD

Unix/Linux

Git

AWS

GCP

Job description

Coderio in the United States is seeking a Senior Data Engineer to design, build, and maintain robust data pipelines and scalable infrastructure across our cloud platform. In this role, you will play a key part in enabling Data Products throughout their lifecycle—sourcing data via batch and stream processing, optimizing data architecture, and ensuring data quality.

Collaborate with Data Scientists and ML Engineers to automate workflows, implement MLOps practices, and monitor pipeline performance.