Senior Data Engineer Brazil

artefactlinkedin; United States; Remote; USD 130,000 - 170,000; Full time

Benefits offered by this job

Remote-first

Meal allowance

Gympass membership

Life, health, and dental insurance

Woba coworking credits

Get Together meetings

Semi-annual reviews with promotions

Job summary

artefactlinkedin is seeking a senior data engineer to design, build, and maintain scalable data pipelines on Google Cloud Platform. You’ll lead end-to-end data workflows within an international, remote-first team.

You will mentor peers, tackle complex engineering challenges, and collaborate with stakeholders across disciplines while delivering production-grade solutions.

Qualifications

• Degree in Computer Science, Statistics, Engineering, Economics, or a related field.
• Excellent Python skills; Java/Scala a plus.
• Hands-on experience with GCP and big data frameworks (Beam/Dataflow, Spark/Dataproc, Flink) and Docker.
• Strong troubleshooting, delivery focus, and mentoring ability.
• Clear communication across diverse teams; fluent English.
• Curiosity, collaboration, and entrepreneurial mindset.

Responsibilities

• Own end-to-end data pipelines and scaling on Google Cloud Platform.
• Build production-grade pipelines using Python and big data tools; containerize with Docker; leverage GKE where applicable.
• Explain technical choices to business stakeholders and collaborate across teams.
• Mentor teammates while delivering hands-on engineering work.
• Navigate Unix-like systems via the command line.
• Prepare high-quality data workflows for analytics and data-driven products.

Skills

Python

Fluent English

Communication

Mentoring

Entrepreneurial mindset

Education

Bachelor's degree in CS/Engineering/Math

Tools

Beam/Dataflow

Spark/Dataproc

Flink

Docker

GKE

Job description

Role overview

A senior data engineering role focused on designing, building, and maintaining scalable data pipelines and workflows that power analytics and data-driven products on Google Cloud Platform. The position supports end-to-end project delivery and a culture of technical leadership and mentoring within an international, remote-first team.

Responsibilities

• Operate across the full delivery value chain, including platform and infrastructure setup, data ingestion, machine learning model application, REST API development, front-end integration, testing, and continuous deployment.
• Build production-grade pipelines using Python, big data tooling such as Beam/Dataflow, Spark/Dataproc, or Flink, and containerization with Docker, with GKE as a plus.
• Explain technical choices to business stakeholders and work alongside colleagues from varied backgrounds.
• Prioritize tasks, respect deadlines, and raise risks before they become issues.
• Mentor and enable teammates while continuing to deliver hands-on engineering work.
• Navigate Unix-like systems confidently through the command line.

Requirements

• Degree in Computer Science, Statistics, Engineering, Economics, or a related field.
• Strong command of Python; experience with Java or Scala is a plus.
• Hands-on experience with GCP and big data frameworks such as Beam/Dataflow, Spark/Dataproc, or Flink, plus Docker.
• Demonstrated ability to troubleshoot complex technical issues and balance delivery with mentoring.
• Solid communication and interpersonal skills for collaborating across multiple teams and seniority levels.
• Fluent English, since the work happens in an international environment.
• Curiosity, collaborative habits, and an entrepreneurial mindset.

Nice to have

• Experience with Google Kubernetes Engine (GKE).
• Java or Scala programming background beyond the core stack.

Benefits and work setup

• Remote-first Free Office arrangement so the role can be performed from home or anywhere.
• Meal allowance (VR).
• Gympass membership and life, health, and dental insurance.
• Woba coworking credits usable in any city.
• Three in-person "Get Together" meetings per year with workshops, talks, training, and social time.
• Semi-annual reviews with promotion opportunities.