Senior Data Engineer (US)

Code and Theory•New York, NY

2d•$120,000 - $160,000

About The Position

As a Senior Data Engineer, you’ll bring deep expertise and strong opinions to complex problems. You’ll lead technical workstreams, mentor others, and help define what great looks like for data engineering. You’ll build scalable data infrastructure that powers data-driven insights and predictive and generative models, working closely with the Machine Learning Engineering team and stakeholders across the agency. Code and Theory is a digital-first creative agency founded in 2001, working across creativity and technology to solve consumer and business problems and establish new capabilities for clients. Its global network includes agencies across North America, South America, Europe, and Asia, and serves clients ranging from Fortune 100 companies to start-ups. The network has nearly 2,000 people, with a workforce described as 50% engineers and 50% creative talent. The compensation range is $120,000–$160,000 and spans multiple levels. The company is open to hiring at the level that best matches the candidate’s experience. Actual compensation depends on factors including skill set, experience, budget, and location.

Requirements

At least 5 years of data engineering experience with a strong record of ownership and impact, including building data pipelines and infrastructure from the ground up.
Deep expertise in cloud data platforms and the ability to explain which platforms work best and why.
Proficiency in Python and SQL for data processing and ETL.
Experience building and deploying data workloads in cloud environments such as AWS, GCP, or Azure.
Strong product orientation and ability to identify opportunities, prioritize initiatives, and deliver measurable business value.
Hands-on experience with AI-powered coding, agentic engineering, and AI-enabled workflows.
Proven experience mentoring others, establishing engineering standards, and contributing to a culture of learning.
Familiarity with marketing data ecosystems, including GA4, advertising platforms, CRMs, and CDPs.
Solid software engineering fundamentals, including version control, testing, code review, and CI/CD.
Strong communication skills and ability to work with all technical levels in an organization described as 50/50 tech and creative.
Experience leading complex, ambiguous projects from definition through delivery.

Nice To Haves

Experience with data governance, privacy compliance, and security best practices.
Experience integrating AI/ML capabilities into data pipelines, with exposure to GenAI applications.
Familiarity with MLOps tooling such as MLflow, SageMaker, or Vertex AI, and with vector databases or RAG patterns.
Experience working across multiple verticals or client types.
Track record of advocating for and implementing process improvements.

Responsibilities

Lead complex workstreams and technical problem-solving across engagements.
Design, build, and scale data pipelines and infrastructure for ingestion, transformation, storage, and serving.
Collaborate with the Machine Learning Engineering team to support model training, evaluation, and serving.
Identify opportunities to improve team processes, tooling, and ways of working.
Contribute to thought leadership, internal knowledge sharing, and community of practice efforts.
Translate business needs into product-minded data solutions that drive measurable business value.
Integrate marketing data sources, including GA4, advertising platforms, CRMs, and CDPs, into reliable, well-modeled datasets.
Establish data engineering standards, documentation, and monitoring practices for data quality and reliability.
Apply AI-powered coding, agentic engineering, and AI-enabled workflows to accelerate delivery.
Mentor others and help establish engineering standards and a culture of learning.