Senior Product Associate - Payments

Join our collaborative environment, where you'll contribute to our strategy and make an impact on product success. Grow your skills, participate in product planning, and define user workflows while working alongside experienced product managers. Don't miss this opportunity to be part of a dynamic team and promote innovation in customer experiences. As a Product Associate in Embedded Payments, you play a crucial role in supporting the product development process and contributing to the discovery of innovative solutions that address customer needs. Working closely with the product management team and cross-functional partners, you contribute your skills and insights to help ensure the success of our product offerings. As a valued member of the team, you have the opportunity to learn and grow in a dynamic and fast-paced environment, making a tangible impact on our products and customer experiences. As a Product Associate in Embedded Payments Analytics Product Management, you will help deliver analytics products that enable self-service insights and decisioning for internal teams. You’ll partner with product, engineering, data engineering, and AI/ML stakeholders to shape capabilities across SQL-driven analytics, Databricks-based data/compute, semantic/metrics layers, dashboards, and AI-enabled analytics experiences. While the role is analytics-forward, you will also develop working knowledge of upstream platform considerations (data quality, lineage, governance, and pipeline reliability) to ensure a great end-to-end user experience. Job responsibilities Supports delivery of analytics products that improve discovery, usability, and trust of data for analysts, data scientists, and business users (e.g., semantic layers, reusable metrics, curated datasets, and analytics tooling). Assists with discovery and user research by gathering stakeholder input, contributing to journey maps, and synthesizing insights into clear problem statements and opportunities. Helps define requirements by writing epics and user stories (with acceptance criteria) that describe analytics workflows, metric definitions, data logic, and reporting needs. Partners with engineering and data teams to translate business questions into implementable analytics solutions, including KPI/metric definitions, dimensional modeling needs, and performance considerations. Considers upstream dependencies (ETL/ELT schedules, data quality checks, schema changes, lineage, and access controls) and helps manage impacts to downstream dashboards, models, and AI consumers. Supports the development of our product strategy and roadmap Collects and analyzes metrics on product performance to inform decision-making Contributes to solution discovery through collaboration with cross-functional teams to identify potential solutions that address user needs and align with business goals Participates in product planning sessions, contributes ideas and insights, and assists in the execution of product initiatives, ensuring timely and successful product launches Collaborates with the product manager to engage stakeholders and define user workflows, requirements, stories, and customer value Required qualifications, capabilities, and skills 1+ years of experience (or equivalent internship/project experience) in product management, analytics, BI, data engineering, or software delivery. Foundational knowledge of the product development lifecycle and comfort operating in Agile teams. Working proficiency in SQL and ability to validate metric logic, perform exploratory analysis, and troubleshoot data issues. Familiarity with analytics concepts: KPIs/metrics, reporting, basic dimensional modeling, and the importance of data quality and definitions. Strong written and verbal communication skills, including the ability to turn ambiguous requests into clear requirements. Developing knowledge level of the product development life cycle Exposure to product life cycle activities including discovery and requirements definition Emerging knowledge of data analytics and data literacy Preferred qualifications, capabilities, and skills Experience with Databricks (notebooks, SQL warehouses, jobs/workflows, Delta tables) or similar lakehouse analytics platforms. Familiarity with semantic/metrics layers and governed self-service analytics patterns (e.g., metric definitions, data catalogs, reusable models). Basic proficiency in Python (or similar) for analytics or automation. Experience with Jira/Confluence for backlog management and documentation. Exposure to AI/ML or GenAI-enabled analytics and awareness of responsible AI considerations.