About the company
Our client is a fast-growing software company.
The role
Raydar is recruiting for this role on behalf of our client. Own the end-to-end data engineering work behind a large analytics and machine learning platform, from bringing in raw records to shaping them for downstream use. You will work closely with data scientists and take responsibility for reliability, speed and quality as data volumes grow.
What you'll do
- Own ingestion, modeling and transformation for a large-scale data asset, extending its attributes and improving the pipelines behind it.
- Expand connections to external business systems as the data footprint grows into multiple terabytes.
- Collaborate with data scientists to move complex workflows into production, scale them and safeguard data quality.
- Create interfaces that let AI-driven applications query and consume data programmatically.
- Contribute to small, focused teams delivering data capabilities tied to significant commercial deals.
- Work with a cloud data warehouse, workflow orchestration and transformation tooling, and a major cloud provider.
Requirements
What we're looking for
- Hands-on experience building and owning ingestion pipelines from start to finish for large, messy data arriving from many sources, including connectors, deduplication, schema changes and reruns.
- Experience as the data engineer creating pipelines that supply machine learning or analytics use cases, such as feature pipelines or model data preparation. Backgrounds limited to modeling, MLOps or LLM infrastructure are not a fit.
- A record of architecting and running data systems that operate reliably at high volume.
- Proficiency with workflow orchestration and transformation tools such as Airflow, Dagster, Prefect, dbt or SQLMesh.
- Experience at a startup, a company known for a high engineering bar, or a data infrastructure vendor.
- Comfort owning analytics engineering and data modeling within a cloud data warehouse.
Bonus points
- Degree from a highly ranked computer science program.
- Experience building supporting infrastructure for AI and machine learning applications, such as retrieval services.
Benefits
Compensation and benefits
- Base salary: USD 200,000 to 250,000 per year
- Equity
- Comprehensive benefits package
Location and work model
- New York, NY, United States
- On-site, 5 days per week in the office
- Full-time
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