Senior Product Manager - eCommerce Data/Artificial Intelligence

Sr. Product Manager - Ecomm Data/AI

Responsibilities :

- Establish the vision for next generation data engineering products. Challenge the status quo and inspire people to think outside the box.

- Efficiently execute to ship products and deliver impact for our data engineers, solving technical and operational problems as they relate to product development.

- Build alignment across product teams, cross-functional partners (Growth, Marketing, Operations, Customer Experience, finance, brands, etc.) and Leadership team

- Communicate concisely with engineering and product leadership, and influence our technical strategy

- Develop the product roadmap and build consensus on prioritisation which drives product execution

- Create processes for collecting feedback from users, and prioritising requests across an expanding number of businesses

- Define key success metrics and SLOs to inform product success and health

Skills :

- 6+ years of product management experience related to data and/or data infrastructure with 5+ years of product management experience in those areas.

- Passionate about improving developer productivity, product quality, and automating/optimizing developer workflows.

- Demonstrated empathy for key data management pain points, and a track record of leadership in building products for data engineers or data scientists

- Drive the taxonomy evolution strategy that enables better detection, routing, and log user issues

- Strong understanding of technical architecture and data infrastructure principles

- Experience with managing multiple product team roadmaps to build cohesive data ecosystems, platforms and tools

- Proven ability to prioritise and pair bold product vision with execution

- Strong written and verbal communication ability to influence and drive strategy

Preferred Experience :

- 5+ years of experience developing data infrastructure products

- Experience as a data engineer, data scientist, or other advanced data user

- Knowledge of data creation and consumption products (Data Integration, Data Warehouse, ETL, Analytics, Reporting, etc.)

- Experience with anomaly detection, observability, and logging tool sets

- Experience with ML products including feature creation and/or model training