Senior Data Engineer - USA

Coderio; Washington (District of Columbia); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Coderio is seeking a Senior Data Engineer in the United States (remote/hybrid) to design, build, and maintain scalable data pipelines across our cloud platform. You will enable data products, source data via batch and stream processing, and collaborate with Data Scientists to automate workflows and deploy resilient pipelines in production.

You will work with Python, PySpark, and SQL to optimize ETL/ELT processes, ensure data quality, and participate in MLOps practices, while contributing to a

Qualifications

• 5+ years of experience in Data Engineering.
• Mastery of Python and advanced SQL.
• Hands-on experience with AWS or GCP and PySpark.
• Proficiency with UNIX, Docker, Git, and CI/CD pipelines.

Responsibilities

• Design, build, and deploy scalable data pipelines for batch and streaming data ingestion into Data Lakes and Data Warehouses.
• Develop and optimize ETL/ELT pipelines using Python, PySpark, and SQL.
• Collaborate with Data Scientists and ML Engineers to build resilient pipelines and MLOps workflows.
• Monitor and optimize pipeline performance, costs, and storage across cloud platforms.
• Implement data quality frameworks and governance across datasets.
• Maintain CI/CD pipelines and document standards.

Skills

Python

SQL

PySpark

Data modeling

ETL/ELT

English communication

Tools

Docker

Git

CI/CD pipelines

Unix/Linux

Terraform

Job description

About Coderio

Coderio 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: http://coderio.com

Job Overview

We 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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.