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Numerator is looking for a Data Engineer II to help us expand and optimize our data platforms, drive decision-making, and enable innovation across our products. In this position, you will take ownership of complex initiatives to automate, enhance, maintain, and scale services in a rapidly evolving environment.

As a Data Engineer II at Numerator, you will build resilient data pipelines, architect infrastructure, and enable advanced analytics and modeling capabilities. You will partner cross-functionally with Product, Analytics, Data Science, and Engineering teams, ensuring the integrity, scalability, and performance of our data systems. This role goes beyond implementation—you will play a key part in shaping data strategies, mentoring team members, and delivering impactful, production-grade solutions.

What You'll Do:

+ Collaborate with cross-functional teams to design, enhance, and scale data products that power analytics and customer-facing solutions.

+ Lead complex, end-to-end projects focused on improving data quality, integrating advanced statistical and machine learning models, and driving measurable business impact.

+ Architect and develop pipelines that enforce robust data validation, quality checks, and efficient workflows for model deployment.

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

+ Mentor junior engineers and contribute to best practices, design standards, and engineering excellence across the team.

+ 3+ years of experience in data engineering, including designing and maintaining data warehouses, building data pipelines, and implementing large-scale data solutions.

+ Proficiency in Python and SQL, with demonstrated expertise in building efficient, high-quality data transformations.

+ Strong background in data modeling, ETL design, and orchestration tools (especially Airflow), ensuring business goals are met with data integrity and scalability.

+ Proven experience deploying cloud-based production solutions in AWS, Azure, or GCP, with emphasis on data reliability across environments.

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

+ Strong problem-solving ability, intellectual curiosity, and attention to detail, with a focus on delivering high-impact solutions in a fast-paced, collaborative environment.

Nice to haves:

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

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

+ 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 environments.

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

+ Ability to contribute to technical strategy and mentor more junior team members.

What we offer:

+ An inclusive and collaborative company culture - we work in an open, transparent environment to get things done and adapt to the changing needs as they come

+ An opportunity to have an impact in a technologically data-driven company that’s changing the market research industry and getting rave reviews

+ Market-competitive total compensation package

+ Volunteer time off and charitable donation matching

+ Strong support for career growth, including mentorship programs, leadership training, access to conferences and employee resources groups

+ Regular hackathons to build your own projects and Engineering and Data Science Lunch and Learns