Data Engineer

Scale Media · United States · $130k – $150k · posted today ago

engineering data remote jobs in united states

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About this role

About Scale:

For the past 12 years, Scale Media has been building and scaling science-backed wellness brands. Our portfolio of brands, including Live Conscious, 1MD, and Essential Elements, has grown to 9 figures in revenue while operating profitably with no external funding.

Our team is made up of operators, marketers, and builders focused on products consumers actually trust. We're investing heavily in data and AI to sharpen how we develop products and scale brands.

We believe the best decisions come from data, curiosity, and continuous learning. We value high ownership, candid feedback, and thoughtful execution. As a fully remote company, we lead with clear communication, accountability, and trust, and we give people real room to grow and make an impact.

Scale Media has been recognized as one of Forbes' Best Startup Employers, a Great Place to Work, an Inc. Best Workplace, and an Inc. 5000 company.

If you take ownership, think for yourself, and like solving hard problems alongside people who do the same, you'll fit right in.

The Role

We're looking for a Data Engineer to own the data infrastructure behind all of Scale Media's brands. You'll build and run the pipelines that bring together data from Shopify, Amazon Seller Central, Meta, Google Ads, Klaviyo, and Odoo, etc. and make sure the teams who rely on that data can trust it.

You'll join our existing engineering team as its dedicated data specialist. That means real ownership: you'll set the direction for how we model, move, govern, and use data, with engineering teammates around you to build alongside.

Most of your time will go to data engineering. You'll also be a thought partner on key cross-functional projects, most notably Odoo, which our inventory team uses for inventory management. There, you'll help plan upgrades, design integrations, and keep its data flowing cleanly into the rest of our stack. This is a hands-on builder role for someone who enjoys solving messy data problems and turning them into reliable systems.

What You'll Own

Data Architecture & Pipelines:

Own and optimize the company's data architecture and ETL/ELT pipelines, including scheduling, orchestration, and monitoring with tools like Airflow and dbt.
Maintain, optimize, and expand our hosting infrastructure and scripts as data volume and use cases grow.
Ensure data accuracy, consistency, and reliability across every source system, so reporting and decisions rest on numbers people trust.

Integrations & Data Connectors:

Maintain API integrations and data connectors with platforms including Shopify, Amazon Seller Central, Meta, Google Ads, Klaviyo, etc.
Scope and build new data integrations as the business adds tools, channels, and brands.

Odoo Partnership:

Act as the go-to technical partner for Odoo, supporting our inventory team on Odoo-related initiatives.
Help plan and execute Odoo upgrades with minimal disruption to day-to-day inventory operations.
Design, build, and maintain integrations and ETL processes between Odoo and our other internal and external systems.

Data Governance & Documentation:

Oversee data governance, access controls, and security practices that protect our systems and customer data from breaches.
Document configurations, integrations, and data flows so the rest of the team can understand and build on them.
Act as a thought partner to analytics and marketing teams to define, standardize, and maintain business-critical KPIs across all data models and reporting layers.

AI/ML & Automation:

Implement AI/ML-driven solutions for data enrichment, anomaly detection, forecasting, and process automation.
Continuously review data workflows and performance, and find new ways to use data to make the business run more efficiently.
Ownership and setup of MCP connection to the data warehouse to allow users access to data through LLM

What You Bring

Strong SQL and Python skills, with hands-on experience building and maintaining production data pipelines.
Experience with modern orchestration and transformation tools such as Airflow and dbt, and with a cloud data warehouse (Snowflake, BigQuery, Redshift, or similar).
Hands-on experience with Odoo, including working with its data model, building integrations, and supporting or executing version upgrades.
Experience working with Shopify data and APIs, and integrating ecommerce and marketing platforms such as Amazon Seller Central, Meta, Google Ads, or Klaviyo.
Comfort managing cloud infrastructure (AWS, GCP, or similar) and the scripts and jobs that run on it.
A solid grasp of data governance, security, and access-control practices.
Clear documentation habits and the ability to explain data systems to non-technical teammates.
3–5 years of experience in data engineering or a closely related role. Strong backgrounds include:
Data engineers at DTC or ecommerce brands who have owned the full stack from source to warehouse
ERP or Odoo developers who have grown into broader data engineering and pipeline work
Analytics engineers who have taken on infrastructure, orchestration, and integration ownership

Preferred, But Not Required

Experience in DTC, consumer subscription, supplements, or wellness.
Experience building custom Odoo modules in Python.
Hands-on work applying AI/ML to forecasting, anomaly detection, or data enrichment.
Familiarity with inventory, supply chain, or demand-planning data.

What Makes You a Fit

High Ownership: As our dedicated data specialist, you treat the data stack as yours to improve, not a ticket queue to work through.
Thought Partner: You bring ideas to the table and help teams like inventory shape the right solution, not just implement the request.
Detail-Oriented: You care about getting the numbers right, because the whole business makes decisions on them.
Self-Starter in a Remote Environment: You're comfortable in a fully remote, fast-paced environment and communicate clearly without needing to be in the same room.
Curious Problem-Solver: You enjoy untangling messy data problems and keep an eye out for new ways data can make the business more efficient.