Remote Data Engineer: Build Trusted Pipelines & AI Tools

Grüns; San Francisco (CA); On-site; USD 150,000 - 170,000; Full time

Benefits offered by this job

Remote HQ

Biannual off-sites

Competitive compensation

Well-being benefits

Job summary

Grüns is seeking a data engineer to design, build, and own data pipelines that feed analytics, AI initiatives, and operations. You will develop Airflow DAGs, dbt models, and a governed semantic layer, partnering with Finance, Operations, Growth, and Tech to turn ambiguous requests into durable data products.

The role is fully remote with biannual off-sites and a collaborative, high-trust culture. You’ll work across BigQuery, GCP, and modern cloud tooling to move fast while maintaining quality.

Qualifications

• 3+ years in data engineering or analytics engineering with production impact.
• Production-quality Python and advanced SQL, maintainable and tested code.
• Design, build, and operate Airflow workflows for data pipelines.
• Strong dbt and dimensional modeling fundamentals, including incremental models and tests.

Responsibilities

• Design, build, and own customer data pipelines into the data warehouse.
• Build and operate Airflow DAGs for scheduled and event-driven workflows.
• Develop dbt models and a governed semantic layer for analysts and AI tools.
• Create patterns for incremental syncs, retries, backfills, and event processing.
• Build monitoring, quality checks, and reconciliation to protect reports and tools.
• Diagnose production incidents and collaborate with cross-functional teams.
• Document decisions and recovery procedures for durable data products.
• Leverage AI coding agents to accelerate implementation while ensuring correctness.

Skills

Python

SQL

Airflow

dbt

BigQuery

GCP

APIs

Tools

Cloud Composer

Job description

Grüns is seeking a data engineer to design, build, and own data pipelines that feed analytics, AI initiatives, and operations. You will develop Airflow DAGs, dbt models, and a governed semantic layer, partnering with Finance, Operations, Growth, and Tech to turn ambiguous requests into durable data products.

The role is fully remote with biannual off-sites and a collaborative, high-trust culture. You’ll work across BigQuery, GCP, and modern cloud tooling to move fast while maintaining quality.