Senior Data Engineer - USA

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

About CoderioCoderio designs and delivers scalable digital solutions for global companies. With a solid technical foundation and a product-oriented mindset, our teams lead complex software projects—from architecture to execution. We value autonomy, clear communication, and technical excellence. We collaborate closely with international teams and partners, building technology that creates an impact.Learn more: Job OverviewWe are looking for a Senior Data Engineer based in the US 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. You will collaborate closely with Data Scientists and ML Engineers to automate workflows and deploy resilient data pipelines in production.

• Work Location / Employment: US-based (Remote / Hybrid) — Must be authorized to work in the United States.

Tech Stack & Key Technologies

• Cloud Platforms: AWS (Redshift, Glue, EMR, MWAA, S3) & GCP (BigQuery, Cloud Storage)
• Languages & Frameworks: Python, PySpark, SQL (advanced optimization & tuning)
• Data Engineering & Ops: Batch & Stream Processing, ETL/ELT Pipelines, Data Modeling, Data Warehousing, Orchestration
• DevOps, Infrastructure & Tools: Docker, Terraform, CI/CD pipelines, UNIX/Linux environments, MLOps best practices

Key Responsibilities

• Pipeline Architecture & Development: Design, build, and deploy scalable, decoupled, and high-performance data pipelines for batch and streaming data ingestion into Data Lakes and Data Warehouses.
• ETL/ELT Processing: Develop and optimize efficient data pipelines using Python, PySpark and advanced SQL.
• Collaboration with ML & Data Science: Partner with Data Scientists and ML Engineers to build resilient pipelines, automate MLOps workflows, and gather model interaction data to support retraining loops.
• Performance Optimization & Monitoring: Continuously monitor, troubleshoot, and optimize pipeline execution, query performance, and storage resource utilization across cloud platforms.
• Data Quality & Governance: Implement data quality frameworks and testing controls to ensure data integrity, reliability, and governance across raw and curated datasets.
• DevOps & Standards: Apply MLOps and DevOps best practices, maintain CI/CD pipelines, use Docker for containerization, and document technical standards and architectures.

Qualifications & Requirements

• Experience: 5+ years of experience in Data Engineering, with a proven track record of designing and running large-scale data systems.
• Core Languages: Mastery of Python and advanced SQL (query optimization and performance tuning).
• Cloud & Big Data Tools: Hands-on experience with AWS (Redshift, Glue, EMR, MWAA, S3) or GCP (BigQuery) and modern data processing engines (PySpark).
• Engineering Ecosystem: Proficiency with UNIX environments, Docker, Git, and CI/CD pipelines.
• Data & ML Lifecycle: Solid understanding of data structures, batch/streaming processing, and familiarity with MLOps or the ML deployment lifecycle.
• Communication: Excellent verbal and written English communication skills.

Nice to Have

• Experience with Infrastructure as Code (e.g., Terraform).
• Experience building and maintaining scalable REST APIs.
• Exposure to prompt engineering workflows or generative AI data pipelines.

Why join Coderio?

At Coderio, we value talent regardless of location. We are a remote-first company, passionate about technology, collaborative work, and fair compensation. We offer an inclusive, challenging environment with real opportunities for growth. If you are motivated to build impactful solutions, we're looking for you.