Senior Data Engineer

We're looking for a Data Engineer to own our data infrastructure end to end. Today our data lives in 15+ disconnected systems, and teams pull the same metrics from different places and get different answers. You'll fix that. You'll build the central data warehouse everyone works from, keep it reliable, and unlock projects that are currently blocked by incomplete data, including our demand forecasting, which is under-ordering our best sellers because it can't see stockouts. This is a high-impact, high-ownership role. You won't be one of ten engineers maintaining someone else's pipeline. You'll build this from the ground up and be the person the entire company depends on for trustworthy numbers.

What You'll Do

Ongoing:

• Build and maintain automated daily pipelines from all sales channels (Shopify, Amazon, eBay, Walmart), ShipHero, Google Analytics, and ad platforms into a central warehouse
• Monitor pipeline health and fix broken feeds same-day, before bad data reaches decision-makers
• Maintain the single source of truth: the official tables every team, report, and forecast runs on
• Support internal data consumers across forecasting, reporting, marketing, and AI projects

Key projects (roughly in order):

• Central data warehouse (first ~2 months): connect every source into one database so data can finally be combined
• Fix forecasting blind spots (months 2-4): capture daily inventory snapshots so stockouts are visible, estimate lost sales from traffic data, and feed in promotions and ad spend so the forecast can distinguish a promo spike from real demand growth
• Connect web behavior to SKUs (months 3-5): match GA4 traffic to products across all channels
• Retire spreadsheet infrastructure (months 4-6): move forecast inputs, container schedules, and dump tables into proper automated systems
• Self-serve dashboards (second half of year 1): automated reporting for customer service, marketing, and inventory teams
• Voice AI measurement (alongside dashboards): call data, sentiment, and AI-vs-human performance metrics
• ShipCore analytics layer (year 2): client-facing reporting and billing data as we take on outside clients, * Real ownership. You're building this, not maintaining someone else's mess.
• Visible impact. Your work directly fixes stockouts on our best-selling products, that's revenue you can point to.
• Growth path. Year 2 turns this role into part of a product our clients pay for.

• Proven experience building and maintaining production data pipelines
• Strong SQL; proficiency in Python or similar
• Experience with cloud data warehouses (BigQuery, Snowflake, Redshift, or similar)
• Experience integrating APIs from multiple third-party platforms
• Comfort working independently and owning infrastructure end to end
• Ability to translate business questions into data models

Nice to Have

• E-commerce or marketplace data experience (Amazon, Shopify)
• Experience with dbt, Airflow, or similar orchestration tools
• Google Analytics / GA4 data experience
• Supabase, Postgres
• Familiarity with demand forecasting or inventory data
• BI/dashboard tools (Looker, Metabase, Power BI, Tableau)

Pulled from the full job description

• Health insurance
• Paid time off
• Employee discount, * Health insurance
• Paid time off
• Sick Days
• Employee discount
• Daily Lunch

Work Location: In person at Fullerton, CA.

Pay: $120,000.00 - $150,000.00 per year

Compensation Package:

• 1099 contract

Coverland is a fast-growing e-commerce company in the automotive accessories space, selling car covers, seat covers, floor mats, and related products across Amazon, Shopify, eBay, Walmart, and direct-to-consumer channels. We're building the data infrastructure to support our next stage of growth.