Senior Data Engineer — Remote, GCP & Data Pipelines

Jobo; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Private healthcare

Insurance

Multisport benefits

Home office equipment

Development budget

Global client exposure

Knowledge sharing sessions

Job summary

Astral Forest Prosta Spóka Akcyjna is seeking a Senior Data Engineer to own and optimize complex data environments in a fully remote role. You will design GCP-based data solutions, build robust pipelines with Python, dbt, and Airflow, and map existing architectures for reliability.

The ideal candidate has 5–6 years in data engineering with strong GCP exposure, data modeling, and security practices, plus the ability to mentor teammates and adapt to varied client projects.

Qualifications

• 5–6 years of Data Engineer experience with strong GCP focus.
• Hands-on Python, dbt and Airflow expertise.
• Solid data modeling, integration and security practices.
• Ability to work independently and mentor teammates.
• Consultant mindset adaptable to client needs and domains.
• Full professional proficiency in English.

Responsibilities

• Design and improve GCP data solutions using BigQuery, Cloud Storage, and Cloud Composer.
• Build and maintain robust pipelines and transformations with Python, dbt and Airflow.
• Take over existing environments, map architectures, document processes, ensure reliability.
• Review colleagues' work and provide constructive feedback to maintain standards.
• Utilize Terraform, GitHub, and CI/CD to manage deployment lifecycles.

Skills

GCP expertise

Python

dbt

Airflow

Data modeling

Mentoring

Independent work

Consultant mindset

English proficiency

Tools

Google Cloud Platform

Python

dbt

Airflow

Terraform

Job description

Astral Forest Prosta Spóka Akcyjna is seeking a Senior Data Engineer to own and optimize complex data environments in a fully remote role. You will design GCP-based data solutions, build robust pipelines with Python, dbt, and Airflow, and map existing architectures for reliability.

The ideal candidate has 5–6 years in data engineering with strong GCP exposure, data modeling, and security practices, plus the ability to mentor teammates and adapt to varied client projects.