GCP Analytics Engineer

xebiacee; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

xebiacee is seeking a data engineer to develop and improve analytical data transformation workflows built around dbt and BigQuery. The role focuses on data modeling, runtime and artifact lifecycle management, execution efficiency, and collaboration with data engineering and platform teams to support governed, reliable analytics.

Responsibilities include designing, developing, and maintaining dbt transformation frameworks and analytical models; building and optimizing models for Silver and Gold

Qualifications

• Strong SQL skills and hands-on dbt experience.
• Experience with BigQuery and building analytical/transformation layers on modern data platforms.
• Experience developing and maintaining data models for enterprise analytics.
• Understanding of model lifecycle management and versioning.
• Familiarity with Docker-based deployment and performance optimization for data transformations.
• Good Python skills and strong communication/documentation.

Responsibilities

• Design, develop, and maintain dbt transformation frameworks and models.
• Build and optimize Silver and Gold data layer models in BigQuery.
• Improve dbt speed and operational efficiency; simplify workflows.
• Manage dbt artifacts, versioning, and lifecycle; separate models from runtime images.
• Coordinate with engineering, DevOps, and platform teams on data quality and governance.

Skills

SQL

dbt

BigQuery

Python

Data modeling

Tools

Docker

Apache Airflow

Kubernetes

Google Cloud Storage

Job description

Role overview

Develop and improve analytical data transformation workflows built around dbt and BigQuery. The role covers data modeling, runtime and artifact lifecycle management, execution efficiency, and collaboration with data engineering and platform teams to support governed, reliable analytics layers.

Responsibilities

• Design, develop, and maintain dbt transformation frameworks and analytical models.
• Build and optimize models for Silver and Gold data layers in BigQuery.
• Improve dbt execution speed and operational efficiency, and simplify transformation workflows.
• Manage dbt artifact versioning and lifecycle; separate models from runtime Docker images and establish controlled distribution.
• Assess when native BigQuery execution approaches are suitable alternatives.
• Coordinate with engineering, DevOps, and platform teams on data quality, governance, and technical documentation.

Requirements

• Strong commercial experience with dbt and strong SQL skills.
• Hands-on BigQuery experience and a background building analytical or transformation layers on modern data platforms.
• Experience developing and maintaining data models for enterprise analytics environments.
• Understanding of model lifecycle management and versioning.
• Experience with Docker-based deployment approaches and performance optimization for data transformations.
• Familiarity with Python and strong communication and documentation skills.

Nice to have

• Apache Airflow experience, including BigQuery job operators or similar orchestration patterns.
• Familiarity with Google Cloud Storage and Kubernetes.
• Experience creating reusable transformation frameworks and optimizing cloud processing costs.
• Background in regulated sectors such as banking, or in data quality and governance initiatives.