Data Engineer

Raydar; New York (NY); On-site; USD 200,000 - 250,000; Full time

Benefits offered by this job

Equity

Comprehensive benefits package

Job summary

Raydar is seeking a senior data engineer to own end-to-end data engineering for a large analytics and machine learning platform. Youll shape raw records into production-ready data, ensuring reliability, speed and quality as volumes grow.

You will partner with data scientists and build interfaces for AI-driven applications, working with cloud warehouses and major cloud providers. You will expand data pipelines, improve ingestion and transform processes, and contribute within focused teams

Qualifications

• Experience owning end-to-end ingestion pipelines for large, messy data.
• Experience delivering ML/analytics pipelines; modeling or MLOps alone is not enough.
• Proven track record running reliable data systems at high volume.
• Familiarity with Airflow, Dagster, Prefect, dbt or SQLMesh.

Responsibilities

• Own ingestion, modeling and transformation for a large-scale data asset and its pipelines.
• Expand connections to external business systems as data footprint grows.
• Collaborate with data scientists to productionize workflows and ensure data quality.
• Create interfaces for AI-driven apps to query and consume data.
• Work with cloud data warehouse, orchestration tools and major cloud providers.

Skills

Ingestion pipelines

Analytics engineering

Data modeling

ML data prep

Cloud data warehouse

Education

CS degree

Tools

Airflow

Dagster

Prefect

dbt

SQLMesh

Job description

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