5+ years of data engineering experience with a proven track record of ownership and impact
Deep expertise in cloud data platforms with strong opinions on their effectiveness
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 deliver measurable business value
Hands-on experience with AI-powered coding and workflows
Proven mentoring experience and establishing engineering standards
Familiarity with marketing data ecosystems (GA4, CRMs, CDPs)
Solid software engineering fundamentals including version control and CI/CD
Strong communication skills for collaboration across technical and creative teams
Responsibilities
Lead complex workstreams and solve technical problems across engagements
Design, build, and scale data pipelines and infrastructure
Collaborate with Machine Learning Engineering to support model training and evaluation
Identify opportunities to improve team processes and tooling
Contribute to thought leadership and internal knowledge sharing
Translate business needs into effective data solutions
Integrate marketing data sources into reliable datasets
Establish data engineering standards and monitoring practices
Apply AI-powered coding and workflows to accelerate delivery
Benefits
Opportunities for mentorship and professional development
Collaborative work environment with a mix of technical and creative professionals
Involvement in thought leadership and community practice efforts
Access to cutting-edge tools and technologies
Potential for flexible work arrangements
Full Job Description
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
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.
