Data Engineer II

Numerator • Chicago, IL

1d

About The Position

As a Data Engineer II at Numerator, you will help deliver data products, analytics, and models quickly and independently. This cross-functional role develops resilient data pipelines and infrastructure for evaluating and deploying data science models. You will work with large quantities of data, build algorithms alongside software engineers, and contribute to data warehouse and service architecture. The role also involves declarative infrastructure, Kubernetes, and using AI tools to work efficiently, as well as helping build internal AI agents.

You will have broad impact across Numerator, helping build and expand technology platforms used by several software products. This is a fast-paced role with growth, visibility, and impact, where you and your team will drive many projects from inception through production.

Requirements

• 2–3 years of experience in data engineering, data warehousing, or related roles, with a strong focus on data quality.
• Proficiency in Python (preferred) or another major programming language, and SQL.
• Experience implementing data validation and transformation processes.
• Experience using AI coding assistants and LLM tools in day-to-day work to ship faster without compromising quality.
• Expertise in data modeling, ETL/ELT design, and workflow orchestration, preferably using Airflow.
• Experience designing and deploying cloud-based production solutions on AWS, Azure, or GCP, with a focus on maintaining data quality across environments.
• Strong attention to detail, intellectual curiosity, and commitment to delivering high-quality data in a fast-paced, collaborative environment.

Nice To Haves

• Experience with AWS or cloud-based certifications, such as AWS Certified Solutions Architect – Associate or AWS Certified Developer – Associate.
• Experience with Terraform, Ansible, or similar tools for infrastructure deployment.
• Experience with Airflow, including building and monitoring DAGs and developing custom operators.
• Experience with Snowflake, Databricks, or another data warehouse.
• Experience with containerized services such as Docker and Kubernetes.
• Familiarity with Tableau or another data visualization tool.
• Experience with marketing insights, shopping data, or the retail industry.

Responsibilities

• Collaborate with Product, Analytics, Data Science, and Engineering teams to build or enhance data products while adhering to data quality standards.
• Lead complex, end-to-end projects to improve data quality and ensure statistical models are supported by clean, validated data.
• Build, deploy, and support internal AI agents and the data pipelines, tools, and infrastructure they rely on.
• Design and develop pipelines that enforce data validation, quality checks, and best practices for integrating Data Science models into customer-facing products.

Benefits

• Volunteer time off and charitable donation matching.
• Mentorship programs, leadership training, access to conferences, and employee resource groups to support career growth.
• Health, vision, and dental benefits.
• Personal Spending Account.
• Unlimited PTO.
• Flexible schedule.
• 401K matching.
• Travel reimbursement.
• Market-competitive total compensation package.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed