Set the strategy and product roadmap for short and long term horizons, influencing C-level leaders on investment allocation
Influence engineering leaders and architects on functional and non-functional requirements for data systems including Data Movement, Processing, Storing and Serving, Agentic & RAG architectures, Analytics, and Data Governance
Develop golden path workflows and fit-for-purpose abstractions for internal developers, non-technical internal users, and external users
Partner with Product leaders to enable new data capabilities across Payments, Connect, Risk, Revenue and Financial Automation
Identify relevant trends in data innovations and open source advancements (e.g., Airflow, Spark, Flink, Iceberg, Trino, Pinot, Jupyter, DBT)
Serve as a founding member of the Product Management discipline and culture for the Data Foundations organization; set technical direction and deliver reliable experiences for customers
Requirements
Passion for and experience shipping technical data products and developer tooling
Strong understanding of modern data platform technologies including high throughput event management, lambda vs kappa architectures, online datastores, data lakes and warehouses, semantic layers, query gateways, data lineage, validation tools
8+ years of Product Management experience
Computer Science background or equivalent technical experience
Strong written and verbal communication skills with the ability to convey complex technical concepts to non-technical stakeholders
A people-first leader with high emotional intelligence and ability to gain trust with senior engineering and technology leaders
Strong storytelling and executive presence skills
Strong product sense, team collaborator, independent, and risk-taking based on data-driven decisions
Experienced product manager discipline in growth technology companies (preferred)
Experienced partnering closely with c-suite technology executives (preferred)
Product skills spanning technical, user experience, business and go-to-market domains (preferred)
Intimate knowledge of data infrastructure technologies (e.g., Iceberg, Airflow, Flyte, Flink, DuckDB) (preferred)
Former software engineer or data engineer (preferred)
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