Data Engineering | Remote, US + customer site travel | Full time | Reports to the CEOOpen roleJOB-2026-DP-001
Design and build the data architecture that connects every model in our suite, from the raw feed to the number on screen. Our suite prices four decisions together: buy, make, sell and risk. Each decision runs on models that read the same market data and the same customer records. You define that data, and you build the pipelines that connect it to every model.
What you'll do
- The Whole Suite: Connect the data for all four pillars: Buy, Make, Sell and Risk
- Data Architecture: Design how data moves from the source to the lake, to the models and to the screen
- Data Definitions: Define each dataset once: its grain, its keys, its owner and its meaning
- Model Inputs: Connect the pricing, risk, forecasting and optimization models to the data they need, at the grain and time they need it
- Market and Customer Data: Connect exchange and government feeds, and each customer's ERP, plant and sales records
- Feature Pipelines: Build the pipelines that deliver features to the models, and keep each run reproducible
- Checks and Lineage: Trace each number to its source, and catch a stale or changed feed before a model reads it
- Our Stack: Python, SQL, dbt, Dagster, Postgres and Databricks on Google Cloud
How we will measure it
- Datasets with one written definition: allFails when two models read the same field differently
- Breaks caught before a model reads them: allFails when a model or a customer finds a break first
- Time from a new data source to a model inputFails when it stays flat or rises
Required
- Designed and built data architecture that production models read
- Defined data models and contracts that more than one team or product used
- Connected messy source systems such as an ERP to clean, modeled data
- Built data as of a point in time, with no lookahead, for series that arrive late or change after release
- Write production SQL and Python every day
Preferred
- A data catalog, a feature store or a model registry in production
- dbt, Dagster, Databricks or Spark
- Commodity, market, manufacturing or freight data
Not the role for you if
- You want to design the system and hand the build to someone else
- You need a full specification before you start
How we hire
- 1 ApplyReply in 5 days
- 2 CEO call45 min
- 3 Working session2 hours
- 4 References1 week
- 5 Offer2 days after refs
Vadar Alpha builds commercial intelligence for companies that make and move physical goods. Our software helps them buy inputs lower, sell outputs higher, and protect every margin in between.
Base salary $140,000 to $180,000, plus equity, performance pay and health coverage (QSEHRA). We review applications through December 31, 2026.
How to apply
Send one thing you built, ran or wrote, and a paragraph on your first 90 days.
- jobs@vadaralpha.com
- Reference
- Sr. Data Products Engineer
- Cover letter
- No cover letter
- Who reads it
- A person reads every application
Vadar Alpha is an equal opportunity employer. Need an accommodation to apply? Email jobs@vadaralpha.com.