Sr. Data Engineer

Numerator is a data and technology company reinventing market research. Headquartered in Chicago, IL, Numerator has 1,600 employees worldwide. The company blends proprietary data with advanced technology to create unique insights for the market research industry, which has been slow to change. The majority of Fortune 100 companies are Numerator clients.

We are seeking a Senior Data Engineer to lead the expansion and optimization of our data platforms, drive data-driven decision-making, and enable innovation across our products. In this role, you will own complex initiatives to automate, enhance, and scale services in a rapidly evolving environment, while mentoring peers and shaping our data strategy.

The Role

As a Senior Data Engineer at Numerator, you will design and build resilient data pipelines, architect infrastructure, and enable advanced analytics and modeling capabilities. You will work closely with Product, Analytics, Data Science, and Engineering teams to ensure the integrity, scalability, and performance of our data systems. Beyond implementation, you will drive technical strategy, mentor engineers, and deliver production-grade solutions with measurable impact.

What You Get to Do

Lead cross-functional initiatives to design, enhance, and scale data products that power analytics and customer-facing solutions.

Own and deliver complex, end-to-end projects focused on improving data quality, integrating advanced statistical and machine learning models, and driving measurable business outcomes.

Architect and develop pipelines with robust validation, quality enforcement, and efficient workflows for model deployment.

Partner with data scientists to streamline model integration, ensuring reliability and performance in production systems.

Define and promote engineering best practices, design standards, and technical excellence across the team.

Mentor and guide junior engineers, fostering technical growth and knowledge-sharing.

What We Require

5+ years of experience in data engineering, including designing and maintaining large-scale data platforms, building advanced data pipelines, and implementing production solutions.

Proficiency in Python and SQL, with expertise in developing efficient, high-quality data transformations.

Strong background in data modeling, ETL / ELT design, and orchestration tools (especially Airflow), ensuring scalability and integrity.

Proven track record deploying cloud-based solutions in AWS, Azure, or GCP, with emphasis on resilience and reliability.

Familiarity with Machine Learning / Statistical Model Development processes and their data dependencies.

Demonstrated leadership in solving complex problems, with intellectual curiosity, attention to detail, and a focus on business impact.

What We’re Looking For

Deep experience with Amazon Web Services (EC2, RDS, ECS, S3, Lambda, etc.).

Expertise in Terraform, Ansible, or similar IaC tools for infrastructure automation.

Advanced proficiency in Airflow, including DAG design, monitoring, and custom operator development.

Hands-on experience with modern data platforms such as Snowflake, Databricks, or Redshift.

Comfort working with containerized services (Docker, Kubernetes) in production.

Background in retail, consumer insights, or marketing data is a strong plus.

Ability to influence technical strategy, drive architectural decisions, and mentor team members.