Junior Data Engineer (dbt, bigquery, paid ads data)

Growth Shop building the data infrastructure that powers smarter decisions for some of the fastest-growing DTC brands in the world… and we need you on the team.

About us:

We’ve helped scale brands like Nectar Sleep (from $10M to $240M in 18 months, exited $1B+) and Victoria Beckham Beauty, along with other high-growth DTC companies. We operate like a technology company—product-driven, data-led, and moving fast—building the Growth Operating System for modern consumer brands.

Your mission:

You’ll work in a fast feedback loop with senior engineers to:

• Set up data extraction (Airbyte, custom Python scripts)
• Build data mapping, modeling, and data marts
• Implement data QA processes to ensure clean, reliable pipelines
• Write efficient SQL, improve dbt models, and orchestrate Airflow DAGs
• Work hands-on with marketing & paid ads data (Meta, Google Ads, etc.)

You’ll learn by doing—whether it’s incremental loading, fixing a broken DAG, or optimizing a BigQuery join that’s too expensive to run daily.

You should have:

• 1–2 years in data/analytics engineering (internship or freelance counts)
• Hands-on experience with marketing or paid ads datasets
• SQL skills (BigQuery preferred)
• Exposure to dbt & Airflow, or the drive to learn fast
• Basic Python scripting skills
• An eye for data quality and testing

Salary: $550 – $900 USD/month

($900 for candidates with deep experience in data engineering for marketing or paid ads data)

What we offer:

• Competitive salary + performance bonus
• Direct mentorship from senior engineers
• 28 days holiday (including public holidays)
• Self-development budget (courses, books, training)
• Fully remote (London & Eastern time zones)
• Payments via Deel (or bank transations)

Application process:

1. Short quiz
2. Interview
3. Simple homework task (dbt modeling)