Remote Data Engineer: Scale AI Data Pipelines

Prolific Academic Ltd; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote working

Job summary

Prolific is seeking a Data Engineer to build scalable data solutions for analytics, ML workloads, and product applications. You’ll work in a cloud-native environment with an emphasis on privacy, security, and robust data practices.

You’ll implement data pipelines with Airflow and dbt, design data APIs, and collaborate across data science, engineering, and product teams to deliver reliable, high-quality data services. Remote-friendly role in the US.

Qualifications

• 3+ years building and shipping production-grade data systems.
• Strong SQL skills and proficiency in Python or Java/Scala.
• Experience with cloud-native infrastructure (Terraform, Kubernetes, Argo).
• Experience designing data APIs or services exposing data to apps.
• Focus on data quality, privacy, and security.
• Strong cross-team collaboration skills.
• Hands-on data pipeline tooling experience (Airflow, dbt).
• Commitment to testing, code reviews and documentation.

Responsibilities

• Build and maintain data pipelines powering analytics, ML workloads, and product apps.
• Evolve data platform using IaC (Terraform) and Kubernetes-based deployments (Argo).
• Design scalable data infrastructure for growing volume and complexity.
• Develop data services and APIs exposing trusted data to applications.
• Own data quality and observability with monitoring, testing, and alerting.

Skills

SQL

Python/Java/Scala

Data pipelines

Data quality & privacy

Independent delivery

Collaboration across teams

Tools

Terraform

Kubernetes

Argo

Airflow

dbt

Job description

Prolific is seeking a Data Engineer to build scalable data solutions for analytics, ML workloads, and product applications. You’ll work in a cloud-native environment with an emphasis on privacy, security, and robust data practices.

You’ll implement data pipelines with Airflow and dbt, design data APIs, and collaborate across data science, engineering, and product teams to deliver reliable, high-quality data services. Remote-friendly role in the US.