Senior Data Product Manager

What You’ll Do Take ownership of and lead the complete analytics instrumentation process for Firefly on web and mobile platforms, covering both client- and server-side implementations — from requirements gathering through specification, validation, and launch. Be the authority on our data. Own what we collect, why we collect it, and how we do it. Proactively find and fill the data gaps that collaborators need to make better decisions. Provide clear mentorship and recommendations on what the data can and can’t tell us. Set the vision, capabilities, and roadmap for product instrumentation, ensuring high‑quality, launch‑ready data is available for every product and feature on day one. Build data products and self‑serve experiences that help users quickly find the right level of data for their needs. This reduces reliance on one‑off, analyst‑led pulls. Define analytics for generative AI. Set the important metrics for a GenAI product, such as activation, engagement, generation quality, and feedback signals. Include credit and consumption economics, and retention. Ensure these metrics are measurable and trustworthy. Champion a consistent taxonomy and high‑integrity data. Optimize the analytics definition process and collaborate with PM and Engineering team members to define clear specifications, governance, and source‑of‑truth practices. Scale our data products to be more accessible, reliable, and digestible for partners across Adobe, with an eye toward automation and AI‑assisted analytics that accelerate time‑to‑insight. What You’ll Need to Succeed 5+ years of product management experience, including building and delivering successful data products, data platforms, and capabilities. 3+ years of hands‑on analytics and technical proficiency in SQL and/or PySpark, data pipelines, and data modeling. Experience working with a contemporary ecosystem for data processing and analysis — such as Databricks, Splunk, Kafka, Adobe Analytics, Customer Journey Analytics, and Tableau — or similar platforms. Demonstrated ability to build and define a consistent taxonomy, and reconcile discrepancies across sources. Practical experience with agile or scrum product development. A strong grasp of foundational statistics and analytics/engineering frameworks. Proven ability to support multiple ongoing projects in a fast‑paced, ambiguous environment. Excellent interpersonal and storytelling skills — able to translate complex findings and technical approaches into clear requirements and compelling narratives for any audience. Strong leadership through influence across functional lines. BS, MS, or PhD or equivalent experience in an analytical field (statistics, applied mathematics, computer science, engineering, economics, physics, etc.). Good to Have Hands‑on experience with data science tooling such as Pandas, NumPy, or similar. Familiarity with the data behind model development — post‑training datasets, the implicit and explicit signals used for RLHF, and model evaluations. Practical understanding of machine learning and statistical analysis (e.g., linear/logistic regression). Experience crafting and using repeatable AI‑enabled workflows using skills and MCPs to scale impact and accelerate delivery. Equal Employment Opportunity Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or any other protected characteristic. Learn more. #J-18808-Ljbffr Adobe