Remote Director, Data Platform & AI Engineering

Grüns; Los Angeles (CA); Remote; USD 180,000 - 220,000; Full time

Benefits offered by this job

Remote HQ

Biannual off-sites

Competitive compensation

Wellness benefits

PTO

Free Grüns product

Job summary

Grüns is seeking a Director of Data Engineering to own the data platform and lead the team building it. We are establishing an enterprise‑level data function with cleaner models and trusted numbers, while maintaining a fully remote HQ culture.

You will drive the data roadmap, refactor legacy pipelines, manage cost, and mentor a small team, all while integrating ERP systems and advancing AI-driven data quality.

Qualifications

• 8+ years in data architecture or data engineering.
• 3+ years leading teams.
• Built and scaled cloud data platforms (BigQuery or similar).
• Strong in SQL, Python, and dbt or similar modeling framework.
• Deep data modeling experience with business-first concepts.
• Data quality, governance, and monitoring practices.

Responsibilities

• Own the data roadmap and company data model with a single source of truth.
• Refactor legacy jobs and reduce tech debt to scale the platform.
• Keep pipelines resilient so data stays available, accurate, and trusted.
• Manage warehouse and infrastructure cost as data volume grows.
• Run intake process and sprint cadence, prioritizing impact across stakeholders.
• Lead and coach a small team with code reviews and growth paths.
• Connect new enterprise systems, such as ERP, into the warehouse.
• Make the team AI-native, using AI agents for development and data quality.

Skills

Data architecture

Data engineering

Team leadership

SQL

Python

dbt

Data modeling

Data quality

Governance

ELT tools

Tools

BigQuery

Fivetran

Orbitrail

dbt

Job description

Grüns is seeking a Director of Data Engineering to own the data platform and lead the team building it. We are establishing an enterprise‑level data function with cleaner models and trusted numbers, while maintaining a fully remote HQ culture.

You will drive the data roadmap, refactor legacy pipelines, manage cost, and mentor a small team, all while integrating ERP systems and advancing AI-driven data quality.