Ensure client-facing platform solutions, audience outputs, reporting workflows, and underlying data processes are accurate, scalable, and operationally sound
Serve as a key bridge between Client Services, Product, Reporting, Data Engineering, and platform operations to ensure platform capabilities are effectively applied to meet client business needs
Oversee the validation and alignment of platform audiences, transaction data, reporting outputs, and campaign performance metrics across systems
Investigate data discrepancies, identify operational risks, establish automated QA and monitoring processes, and help drive scalable workflows that improve confidence in client-facing outputs
Own and oversee client-specific platform execution requirements to ensure platform capabilities are configured, monitored, and leveraged appropriately for business goals
Partner with Client Services, Product, and Sales teams to translate client needs into scalable platform workflows and operational processes
Support audience strategy execution through validation of audience logic, analysis & development of segmentation strategies, and data enrichment methodologies
Apply data engineering concepts and analysis to help operationalize new datasets, overlays, enrichment strategies, and targeting enhancements within platform workflows
Validate and reconcile audience counts, transaction counts, reporting outputs, and platform-generated metrics against campaign reporting, matchback reporting, ROI analysis, and transaction-derived performance metrics
Build and maintain scalable QA, monitoring, and anomaly detection processes
Leverage coding languages and AI-based productivity tools to accelerate data validation and automate checks for missing files, ingestion failures, or logic mismatches
Create repeatable documentation, workflows, and escalation paths to improve consistency and reduce operational risk
Partner with Product and Engineering teams to communicate platform gaps, workflow inefficiencies, and enhancement opportunities uncovered through client usage
Communicate complex data, code, and platform issues clearly to both technical and non-technical stakeholders
Requirements
4+ years of experience in Client Services, Marketing Operations, Data Operations, Platform Operations, Solutions Management, Analytics, or related fields
Bachelor’s degree in computer science, Engineering, Information Systems, or a bachelor’s degree in business, or business-related field, with demonstrated technical experience
An MBA or technical graduate degree is a plus
Strong Technical Aptitude: Hands-on experience with data engineering and analysis principles, including proficiency in coding languages such as SQL and Python for data manipulation and validation
AI Tool Fluency: Experience and working knowledge of AI-based development and productivity tools (e.g., Cursor, Claude Code, GitHub Copilot) to build efficiencies in coding, data analysis, and workflow automation
Experience working with client-facing data platforms, marketing technology platforms, CDPs, audience platforms, or reporting environments
Experience working with identity resolution, audience targeting, enrichment data, matchback reporting, attribution, or campaign analytics
Experience in marketing technology, advertising technology, customer data platforms, or data-driven media environments
Experience building operational processes, data pipelines, or scalable QA workflows in a fast-growing organization
Strong analytical skills with the ability to investigate complex data issues across multiple systems and data sources
Strong organizational skills to manage multiple priorities in an ambiguous environment, paired with excellent client-friendly communication.
Tech Stack
Python
SQL
Benefits
free medical, dental, and vision plan
401(k) with a generous company match of up to 5%
flexible paid time off policy for vacation, illness, and personal needs