Technical Product Manager - Data Foundations

Booking Booking · Hospitality · Amsterdam, Netherlands · Product

Technical Product Manager for Lineage Sourcing product within Booking.com's Data Foundations group. This role focuses on setting product vision, GTM strategy, and driving adoption of enterprise-wide lineage tooling for OLTP and OLAP data and AI systems. The product aims to enable managed sourcing of table and column level lineage, powering data & AI product discovery, impact analysis, and enhancing trust and governance across the enterprise data landscape. The role requires balancing needs of data & AI practitioners and compliance/control/legal functions, with a deep understanding of large-scale distributed enterprise data systems.

What you'd actually do

  1. set the product vision, GTM strategy and drive adoption of enterprise wide lineage tooling, across OLTP and OLAP data and AI systems, and its integration with various other governance tooling like the enterprise policy platform, the enterprise knowledge graph and the enterprise wide data & AI product discovery UX.
  2. enable managed sourcing of table and eventually column level lineage (where applicable) from the majority of multi-modal data production and consumption pathways across the enterprise - across data storage systems (OLTP/OLAP/HTAP) and across workloads running OLTP (Java, Python) and OLAP / HTAP workloads (Spark, dbt, python, SQL etc).
  3. surfacing crucial lineage information to power data & AI product discovery experiences, visibility around movement / transformation of data as it moves through systems enterprise wide, and serve multiple personas from control functions to legal functions to application developers to data / reporting analysts to data engineers and ML/AI engineers / scientists and of course governance personas across the business, which fosters trusts in the data / AI product being used, enables targeted impact analysis before a change needs to be introduced and elevates the overall trust and governance posture of the data landscape enterprise wide.
  4. balancing value elements for the both user segments - the data & AI practitioners of the business as well as the compliance / control / legal functions.
  5. identifying opportunities for their product(s), be deeply passionate about understanding specific needs for each segment of their target customer base, while solving for the compliance challenges around multi-modal data processing the enterprise and our users face today.

Skills

Required

  • Experience with distributed data & AI Platforms
  • wide and deep understanding of various distributed data processing and AI processing capabilities
  • Understanding of data processing in production, at scale
  • Understanding of batch and stream processing, as well as native cloud solutions
  • Demonstrated experience in delivering 0→1 products in an enterprise data & AI platform, at a significant scale
  • Demonstrated ability to navigate complex, matrixed product and engineering organizations
  • ability to navigate significant complexity, driving end user value in demanding environments
  • Solid understanding of various data, analytical and AI assets / products (from datasets > workflows / pipelines > metrics > reports > prompts > features > agents) and how their dependencies are intertwined in a distributed data & AI platform
  • Strong understanding of asset discovery funnels across various journeys on distributed data & AI platforms, across a wide range of personas, and how classification feeds semantic context of various assets, to make such discovery journeys more relevant, context aware
  • Ability to identify core success metrics across various parts of data production and consumption funnels
  • Experience with public Cloud offerings (AWS and GCP) and building on top of cloud platform primitives
  • 6+ years of experience in a Product Management, Engineering or Technology Strategy role
  • Good knowledge of data science / analytics techniques
  • Master of making data-driven decisions, managing backlog, setting and monitoring KPIs
  • Experience with stakeholder management (finance, budgeting, team management, recruitment, external customers)
  • Strong teamwork and collaboration skills
  • Ability to rapidly adapt to the evolving technology landscape

Nice to have

  • passion for identifying opportunities for their product(s)
  • deeply passionate about understanding specific needs for each segment of their target customer base
  • solving for the compliance challenges around multi-modal data processing the enterprise and our users face today
  • User-focused individual who keeps the customer at the heart of everything they do, while having strong commercial awareness
  • Data-driven. Base your decisions on facts rather than opinions
  • A go-getter who isn’t afraid to roll up sleeves and dives into a project to achieve success by problem solving
  • Passionate about data & machine learning and building a platform that can be leveraged by the whole company
  • Constantly looking for ways to improve and streamline the capabilities
  • Open-minded team player with excellent communication skills
  • Agile and innovative with the tenacity to thrive in a constantly changing environment
  • Self-motivated and results-driven with a take charge attitude to manage the full development cycle of a product
  • Friendly, knowledgeable, and motivational to others
  • Open to diversity in all shapes and sizes
  • keep abreast of the rapidly evol

What the JD emphasized

  • enterprise wide lineage tooling
  • data & AI systems
  • data & AI product discovery
  • multi-modal data processing

Other signals

  • enterprise grade data & ML platform
  • foundational capabilities
  • data producers and consumers
  • data & AI systems
  • data & AI product discovery
  • data & AI practitioners
  • distributed data & AI platforms
  • data processing in production, at scale
  • data, analytical and AI assets / products