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Numerator

Data Engineer II

Numerator Chicago, Illinois, United States · $106K–$146K/yr

Technology, Information and Internet · 5,001-10,000 employees

Yesterday
data-engineer Mid (2-5 yrs) Full-time United States
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About the role

You will collaborate with cross-functional teams to build and enhance data products while ensuring high data quality standards. Additionally, you will design and deploy internal AI agents and the infrastructure required to support them.

What they look for

Data Engineering Data Pipelines Data Science Data Warehousing Kubernetes Infrastructure as Code AI Agents Algorithm Development Data Quality Statistical Modeling Software Engineering Data Validation

Requirements

The ideal candidate has experience processing large datasets, building algorithms, and working with data warehouse architecture. Proficiency in declarative infrastructure and Kubernetes is required to support the development of scalable data platforms.

Full description

The salary range for this role is $106,000 - $146,300 + Bonus

As a Data Engineer II at Numerator, you will help our team deliver data products, analytics, and models quickly and independently. The role is cross-functional and responsible for developing resilient data pipelines and infrastructure for evaluating and deploying data science models.

The ideal candidate should be experienced with processing large quantities of data, building algorithms alongside software engineers, data warehouse and/or service architecture, and using declarative infrastructure and Kubernetes.They should also be someone who uses AI to work faster and smarter every day, and who is excited to help build the internal AI agents that are changing how Numerator works.

You will have a broad impact and exposure across Numerator as you help build out and expand our technology platforms across several software products. This is a fast-paced role with high growth, visibility, and impact, and where many of the decisions for new projects will be driven by you and your team from inception through production.

How You’ll Spend Your Time:

Collaborate with Product, Analytics, Data Science, and Engineering teams to build or enhance data products while ensuring adherence to data quality standards

Lead complex, end-to-end projects focused on improving data quality and ensuring statistical models are supported by clean and validated data

Build, deploy, and support internal AI agents, along with the data pipelines, tools, and infrastructure they rely on to deliver reliable, accurate results

Design and develop pipelines that enforce data validation, quality checks, and best practices for integrating Data Science models into customer-facing products

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