Accountabilities:

As a strategic product leader, you will oversee the development and lifecycle management of data platform products while ensuring alignment between technical capabilities and organizational priorities. Your responsibilities will include:

Define and drive product strategy, priorities, and roadmaps across four key domains: data engineering, search, experimentation, and site reliability.

Ensure the accuracy, reliability, accessibility, and practical value of data products and services.

Lead product lifecycle management for the technologies, tools, and services developed by Data Platform Engineering teams.

Collaborate with the Director of Engineering for Data Platform Engineering to establish strategic direction, facilitate decisions, and ensure effective execution.

Guide the evolution of data infrastructure, including data pipelines, data lakes, experimentation platforms, and analytics tools.

Oversee product capabilities covering data ingestion, orchestration, computation, and serving across technologies such as Kafka, Flink, Hadoop, Spark, Airflow, Iceberg, Kubernetes, Superset, dbt, and OpenSearch.

Partner with user-facing product teams, researchers, and data analysts to leverage platform capabilities for product decisions and the development of derived-data products.

Manage, mentor, and develop a team of two individual-contributor Product Managers.

Foster effective collaboration across engineering, research, analytics, and product teams to deliver impactful solutions.

Promote iterative product delivery, prioritizing minimum viable solutions that create value for internal customer teams.

Communicate product strategies, roadmaps, priorities, and decisions clearly to technical contributors, volunteer communities, and organizational leadership.

Requirements

The ideal candidate combines strong technical product management expertise with proven people leadership, strategic thinking, and the ability to navigate complex data ecosystems. You should bring:

At least 5 years of product management experience focused on data, infrastructure, or analytical products.

Demonstrated experience hiring, managing, and developing Product Managers.

A successful track record of delivering data platforms, analytical products, and services used by multiple product teams.

Strong expertise in data analytics, A/B testing, search technologies, and data architecture.

A solid understanding of modern techniques and technologies for processing, managing, and serving high-volume data.

Technical familiarity with data engineering ecosystems, including data pipelines, orchestration, distributed computing, and analytics infrastructure.

Knowledge of search technologies and their application within large-scale digital products.

Experience addressing privacy considerations related to data collection, retention, access, and distribution.

Strong stakeholder management skills and the ability to achieve results through collaboration and influence across multiple teams.

Excellent asynchronous communication skills and the ability to work effectively within a geographically distributed organization.

Sound judgment and decision-making abilities, particularly when dealing with incomplete, ambiguous, or conflicting information.

Strong written communication skills, with the ability to document strategies, plans, roadmaps, and decisions for audiences with different levels of technical expertise.

A commitment to iterative delivery, practical prioritization, and continuous improvement.

Alignment with the mission and values of open knowledge, collaboration, and free access to information.

Additional assets:

Experience working with open-source software, open data, or open knowledge communities.

Experience developing products for multiple languages, regions, and international audiences.

Familiarity with integrating machine learning or artificial intelligence capabilities into web products.

Experience editing Wikipedia or participating in Wikipedia, Wikidata, Wikimedia Commons, or other collaborative knowledge communities.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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