Data Engineer

Posted 2 Days Ago
New York, NY, USA
In-Office
200K-250K Annually
Entry level
Professional Services • Consulting
The Role
Own end-to-end data engineering for a large-scale analytics and machine learning platform. Build ingestion, modeling, transformation, and workflow pipelines; integrate external systems; ensure reliability, scalability, and data quality; and support production machine learning workflows. Develop programmatic interfaces for AI applications and manage analytics engineering within a cloud data warehouse.
Summary Generated by Built In

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

Skills Required

  • Hands-on experience building and owning end-to-end ingestion pipelines for large, messy data from multiple sources
  • Experience building data pipelines supporting machine learning or analytics use cases
  • Experience architecting and operating reliable, high-volume data systems
  • Proficiency with workflow orchestration and transformation tools such as Airflow, Dagster, Prefect, dbt, or SQLMesh
  • Experience at a startup, high-engineering-bar company, or data infrastructure vendor
  • Experience with analytics engineering and data modeling in a cloud data warehouse
  • Degree from a highly ranked computer science program
  • Experience building infrastructure for AI and machine learning applications, such as retrieval services
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The Company
28 Employees
Year Founded: 2021

What We Do

Raydar is a talent acquisition and business consulting firm that connects world-class and emerging talent with growing organizations. It supports companies through team development, strategic hiring, and customized growth solutions, helping clients recruit roles such as engineers, product managers, executives, legal counsel, and quantitative traders. Raydar focuses on understanding each organization’s needs, culture, and long-term goals to build high-impact teams.

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