Remote Data Architect - GCP/BigQuery & Data Mesh

Jobo; United States; Remote; USD 130,000 - 180,000; Full time

Benefits offered by this job

Remote-first

Healthcare

Training budget

Equipment provided

Conferences

Job summary

Astral Forest is seeking a skilled Data Architect to design scalable, cloud-native data ecosystems and shape the data strategy for our global clients. You will design architectures using Google BigQuery and the GCP stack, build data pipelines, and implement governance, security, and cost optimization.

Responsibilities include creating Data Warehouses, Data Lakes, and Data Mesh solutions, optimizing performance and storage, and ensuring data quality.

Qualifications

• 4–5 years in data architecture or advanced data engineering, preferably in GCP/BigQuery environments.
• Strong background in data modeling, ETL/ELT design, and metadata-driven frameworks.
• Proficiency in SQL and exposure to AI/LLM-based solutions.
• Full English proficiency at a B2/C1 level.
• Strong analytical and problem-solving skills with strategic thinking.

Responsibilities

• Design and implement data architectures using Google BigQuery and the GCP ecosystem (Cloud Storage, Dataflow, Composer, Pub/Sub, Dataproc).
• Build scalable, efficient data pipelines and automate workflows using metadata-driven orchestration frameworks.
• Design and develop Data Warehouses, Data Lakes, and Data Mesh solutions meeting business and technical requirements.
• Optimize query performance, data storage, and cost efficiency within BigQuery.
• Ensure high standards of data quality, security, and governance (IAM, DLP, Data Catalog).

Skills

Data modeling

ETL/ELT design

SQL

AI/LLM exposure

Analytical thinking

Strategic thinking

Tools

Google BigQuery

GCP

Cloud Storage

Dataflow

Composer

Pub/Sub

Dataproc

Data Catalog

IAM

DLP

Job description

Astral Forest is seeking a skilled Data Architect to design scalable, cloud-native data ecosystems and shape the data strategy for our global clients. You will design architectures using Google BigQuery and the GCP stack, build data pipelines, and implement governance, security, and cost optimization.

Responsibilities include creating Data Warehouses, Data Lakes, and Data Mesh solutions, optimizing performance and storage, and ensuring data quality.