Senior Data Engineer (US)
Code and Theory Open At a glance
Senior Data Engineering role at Code and Theory. New York · $120,000–$160,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Lead technical work across complex engagements, solving difficult data engineering problems and guiding other engineers
- Build and scale pipelines for ingesting, transforming, storing, and serving data
- Partner with machine learning engineers on data for model training, evaluation, and deployment
- Connect marketing sources such as GA4, ad platforms, and CRMs into dependable, well-structured datasets
- Set practices for data quality and reliability, while improving team workflows and sharing engineering knowledge
What you bring
- At least five years in data engineering, including ownership of pipelines and infrastructure built from the ground up
- Strong Python and SQL skills for data processing and ETL, plus experience deploying workloads on a cloud platform
- Deep knowledge of cloud data platforms and the ability to explain which options suit different work
- Practical use of AI-assisted coding and agent-based engineering workflows
- Experience mentoring engineers, setting technical standards, and taking ambiguous projects from definition to delivery
Who this fits
This role suits a senior engineer who can lead technical work while mentoring others and turning business needs into useful data products. The position is based in New York.
From the employer
As a Senior Data Engineer on our team, 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 the scalable data infrastructure that powers data-driven insights and predictive and generative models, working closely with our Machine Learning Engineering team and stakeholders across the agency.
WHAT YOU'LL DO
- 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 elegant, product-minded data solutions that drive measurable business value
- Integrate marketing data sources (GA4, advertising platforms, CRMs, 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
WHAT YOU'LL NEED
- 5+ years of data engineering experience with a strong track record of ownership and impact, including building data pipelines and infrastructure from the ground up
- Deep expertise in cloud data platforms, with clear, well-reasoned opinions on which work best and why
- Proficiency in Python and SQL for data processing and ETL
- Experience building and deploying data workloads in cloud environments (AWS, GCP, or Azure)
- Strong product orientation, with the 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 (GA4, advertising platforms, CRMs, CDPs)
- Solid software engineering fundamentals: version control, testing, code review, and CI/CD
- Strong communication skills, with the ability to work with every technical level at an organization that is 50/50 tech and creative
- Experience leading complex, ambiguous projects from definition through delivery
NICE TO HAVE
- 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 (MLflow, SageMaker, Vertex AI) and vector databases or RAG patterns
- Experience working across multiple verticals or client types
- Track record of advocating for and implementing process improvements
ABOUT US
Born in 2001, Code and Theory is a digital-first creative agency that sits at the center of creativity and technology. We pride ourselves on not only solving consumer and business problems, but also helping to establish new capabilities for our clients. With a global client roster of Fortune 100s and start-ups alike, we crave the hardest problems to solve. We have teams distributed across North America, South America, Europe, and Asia. The Code and Theory global network of agencies is growing and includes Kettle, Instrument, Left Field Labs, Create Group, Current, and TrueLogic.
Striving never to be pigeonholed, we work across every major category: from tech to CPG, financial services to travel & hospitality, government and education to media and publishing. We value the collaboration with our client partners, including but not limited to Adidas, Amazon, Con Edison, Diageo, EY, J.P. Morgan Chase, Lenovo, Marriott, Mars, Microsoft, Thomson Reuters, and TikTok.
The Code and Theory network is comprised of nearly 2,000 people with 50% engineers and 50% creative talent. We’re always on the lookout for smart, driven, and forward-thinking people to join our team.
The compensation range for this role is $120,000 - $160,000 and spans multiple levels. We're open to hiring at the level that best matches the right candidate's experience. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, budget, and location.
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