Data Engineer

About Us
We're emater — the parent company behind four DTC brands creating global impact. We handle everything in-house from A to Z: operations, marketing, product development, and customer experience.
Based in Miami with offices in Armenia and Israel, and a team spanning the globe, we're redefining what's possible in e-commerce.
How we do it: we combine AI, creativity, and deep customer understanding to deliver results that matter.
Our culture: We invest in our people as much as our brands. Every team member has real opportunities to grow, innovate, and make an impact.
We are seeking a Data Operations & Analytics Engineer to own the accuracy and availability of our business data. This is a role for a builder who loves dirty data as much as clean insights.
Your primary mission is to build the "Source of Truth".
You will engineer the pipelines that move data from our e-commerce and ad platforms into BigQuery (or an alternative data lake), and you will specifically lead the critical project of systematizing our financial data - ensuring every dollar in Shopify matches every dollar in QuickBooks.
Once the data is clean, you will build the dashboards that drive our product and marketing strategy.
Key Responsibilities
1. Financial Data Systematization (The Critical Mission)
E-commerce Reconciliation: Automate the flow of transactional data from Shopify, payment processors and other software into QuickBooks or alternative bookkeeping software.
Complex Mapping: Write logic to correctly categorize Gross Sales, Refunds, Shipping Income, Taxes, and Gateway Fees so our P&L is generated automatically and accurately.
Inventory Reconciliation: Ensure COGS (Cost of Goods Sold) data flows correctly from our inventory systems (Finale/ShipStation) into our financial reporting.
2. Data Engineering & ETL (The Infrastructure)
Pipeline Management: Design, build, and maintain ETL pipelines to ingest data into Google BigQuery from various sources (Meta Ads, Google Ads, TikTok, Klaviyo, etc.).
Cloud Architecture: Utilize Google Cloud Platform (Cloud Functions, Cloud Scheduler) to automate data refreshes and transformation jobs.
Data Quality Assurance: Implement automated tests to catch data discrepancies. If the numbers break, you are the first to know and the one to fix it.
3. Analytics & Business Intelligence (The Insights)
Product Analysis: Analyze lifecycle metrics for our brands. Identify trends in seasonality, repeat purchase rates, and product affinity (cross-selling opportunities).
Dashboarding: Build and maintain high-utility dashboards (Looker Studio/Tableau) for Finance, Marketing, and Support.
Ad-Hoc Analysis: Answer complex business questions via SQL (e.g., "What is the LTV of customers who bought Product X in Q4?").
Required Skills & Qualifications
Data Stack: Advanced SQL and Python (Pandas/Dataframes) are essential.
Cloud Experience: Experience with Google Cloud Platform (BigQuery) and modern ETL tools.
Financial Literacy: You must understand e-commerce finance. You know the difference between an Order Date and a Settlement Date, and you understand how COGS impacts Net Profit.
Visualization: Ability to create clear, actionable visualizations that stakeholders can understand without explanation.
Attention to Detail: You are bothered when numbers don't add up, and you don't stop until you find the variance.
What We Offer
Paid days off, medical insurance, yearly bonus, wellness benefits, and referral bonuses.
A collaborative, supportive environment where your ideas and professional growth are highly valued.

Skills
Python, GCP, SQL, ETL, Pandas, Tableau, QuickBooks

Employment type
Full-Time

Work arrangement
No