Senior Data Engineer (Remote/US) - Scalable Data Pipelines

Coderio; United States; Hybrid; USD 140,000 - 190,000; Full time

Job summary

Coderio in the United States is seeking a Senior Data Engineer to design, build, and maintain robust data pipelines and scalable cloud infrastructure. You will enable data products across their lifecycle, sourcing data via batch and streaming processing, and collaborating with Data Scientists and ML Engineers to deploy resilient pipelines.

This role requires 5+ years in data engineering, strong Python and SQL, and hands-on experience with AWS or GCP, PySpark, and modern data tooling.

Qualifications

• 5+ years of experience in Data Engineering and building large-scale data systems.
• Mastery of Python and SQL with performance optimization.
• Hands-on with AWS or GCP and PySpark.
• Experience with UNIX, Docker, Git, and CI/CD pipelines.
• Strong communication in English.

Responsibilities

• Pipeline Architecture & Development: Design, build, and deploy scalable, decoupled data pipelines for batch and streaming ingestion into Data Lakes and Data Warehouses.
• ETL/ELT Processing: Develop and optimize data pipelines using Python, PySpark, and advanced SQL.
• Collaboration with ML & Data Science: Partner with Data Scientists and ML Engineers to build resilient pipelines and automate MLOps workflows.
• Performance Optimization & Monitoring: Monitor and optimize pipeline execution, query performance, and storage usage across cloud platforms.
• Data Quality & Governance: Implement data quality frameworks and testing controls across raw and curated datasets.
• DevOps & Standards: Apply MLOps and DevOps best practices, maintain CI/CD pipelines, document standards and architectures.

Skills

Python

PySpark

SQL

Data Modeling

Batch Processing

Streaming

Data Warehousing

MLOps

CI/CD

Unix/Linux

Git

Tools

AWS

GCP

PySpark

Docker

Terraform

CI/CD

Unix/Linux

Git

BigQuery

Redshift

Job description

Coderio in the United States is seeking a Senior Data Engineer to design, build, and maintain robust data pipelines and scalable cloud infrastructure. You will enable data products across their lifecycle, sourcing data via batch and streaming processing, and collaborating with Data Scientists and ML Engineers to deploy resilient pipelines.

This role requires 5+ years in data engineering, strong Python and SQL, and hands-on experience with AWS or GCP, PySpark, and modern data tooling.