Kueski

Product Manager

• Own outcomes for Vertical Platform domains, translating company strategy into clear goals.
• Drive prioritization and resource allocation aligned with growth.
• Champion a user-first approach, ensuring high-quality experiences.
• Build a strong data-informed culture, leveraging analytics.
• Build and develop high-performing PM teams.

Senior Director of Product Management

Data Engineer

• Define and drive the data engineering technical strategy, architecture decisions, and platform roadmap aligned to company objectives
• Lead and deliver large-scale, complex data initiatives—spanning multiple teams and iterations—from ambiguous problem definition through production deployment
• Design robust, scalable data architectures (batch and streaming) that support Kueski's long-term business needs at scale
• Demonstrated success shaping and executing an AI-centric data strategy that leverages the latest AI technologies to accelerate value delivery, enable trusted self-service data consumption, and strengthen data quality, governance, and organizational decision-making.
• Identify the limits of existing tools or processes; lead the design and build of new capabilities when current solutions fall short
• Shape, standardize, and champion data engineering methodologies, best practices, and technical standards for the team and department
• Develop and own CI/CD pipelines and infrastructure-as-code for reliable, automated data platform operations
• Drive data quality, observability, and governance programs across the data platform
• Apply data cleansing techniques to facilitate data consumption and quality across the platform
• Partner cross-functionally with Data Science, ML, Analytics, Platform, and Product teams to deliver data-driven solutions end-to-end
• Represent data engineering in cross-organizational initiatives; support and lead efforts outside the core area of responsibility
• Mentor and guide Data Engineers at all levels; constructively challenge assumptions and elevate team quality through code review, pairing, and coaching

Staff Data Engineer

Data Analyst

• Design, implement, and continuously refine marketing attribution models across all channels, ensuring they reflect the true complexity of the customer journey.
• Develop a framework to identify and account for second-order effects initiatives whose impact on brand awareness, funnel priming, or downstream conversion isn't directly attributable but is strategically significant.
• Define incrementality measurement approaches (geo holdouts, intent-to-treat analyses, synthetic controls) to evaluate the true causal impact of marketing investments beyond last-touch or even multi-touch models.
• Own attribution methodology decisions and communicate trade-offs clearly to stakeholders and leadership.
• Lead the implementation and maintenance of tracking infrastructure: pixel setup, tag management (Google Tag Manager or equivalent), and event tracking across web and app.
• Design and implement server-to-server (S2S) integrations to improve signal quality, reduce data loss from browser restrictions, and enhance campaign optimization inputs for paid media platforms.
• Audit and troubleshoot data discrepancies across tracking systems, ensuring data accuracy and integrity end-to-end.
• Manage and evolve the marketing analytics stack (GA4, Amplitude, third-party attribution tools, Databricks) and stay current on emerging measurement technologies and privacy-driven changes.
• Partner with Data Engineering and Product to improve event schemas, tracking coverage, and data pipeline reliability.
• Pull, structure, and analyze your own data independently building the analyses needed to reach conclusions and push initiatives forward, without relying on others to surface information.
• Develop and maintain dashboards and reports that give clear, actionable visibility into campaign performance, channel ROI, and attribution trends.
• Identify patterns and anomalies proactively; bring forward recommendations with a clear point of view, not just observations.
• Use advanced analytics to correlate marketing activities with business outcomes, providing the strategic inputs needed for budget allocation and channel mix decisions.
• Collaborate with Performance and Lifecycle marketing teams to translate attribution insights into concrete campaign optimizations.
• Conduct A/B and multivariate experiments to validate attribution assumptions and improve measurement accuracy over time.
• Help forecast marketing budgets based on attribution data and provide a clear framework for where to allocate spend for maximum ROI.
• Act as the internal expert on attribution and measurement educating teams on best practices and building shared understanding across marketing, data, and finance.

Senior Director of Product Management

Staff Data Engineer

Paid Analytics Manager