Skills this job asks for
A/B testingLeadershipData engineeringKafkaSparkAirflowKubernetesdbtProduct management
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Where you can work from
Location not specified
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The company's headquarters is not the same as where you may work from. Visa sponsorship only matters if you would relocate; see below.
Visa sponsorship, if you would relocate
Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 2 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
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✓
What Wikimedia Foundation paid sponsored hires in similar roles1 certified filing for “Senior Data Scientist” (Statisticians) in NY: $161k–$161k, median $161k.
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✓
Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 2 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Wikimedia Foundation paid sponsored hires in similar roles
- 1 certified filing for “Senior Data Scientist” (Statisticians) in NY: $161k–$161k, median $161k. Most were filed at wage level II (100%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.
About the role
Summary
Wikipedia and its sister projects are among the most popular media properties in the world, visited by over 1 billion people a month across over 300 different languages. These sites generate a tremendous amount of data on how people learn and collaborate. The Wikimedia Foundation is looking for a group product manager to guide the development and evolution of our data platforms , the collection of technologies we use to understand how Wikipedia works, improve its experiences, and spread free knowledge.
The group product manager is a leader in the strategic decision-making and tactical execution for the Data Engineering, Experimentation, Search, and Data Platform Site Reliability teams. This role shares leadership responsibility with the Director of Engineering for Data Platform Engineering, and works in collaboration with data analysts, researchers, and product teams building user-facing features for reading and editing Wikipedia on the web and mobile apps. This is a people management role, managing two individually-contributing product managers.
In this role, you and your group of product managers will guide the evolution of our data pipelines, data lake, experiment platform, and analytics tools. This includes ingestion, orchestration, computation, and serving data using a variety of technologies such as Kafka, Flink, Hadoop, Spark, Airflow, Iceberg, Kubernetes, Superset, dbt, and OpenSearch. A strong candidate will have deep experience building a data platform to serve product analytics and production needs, and be technically conversant in the relevant technologies.
This position will report to the Senior Director of Product, Core Experiences.
Candidates must be available for critical meetings and synchronous work between 15:00 UTC and 18:00 UTC, and open to traveling internationally up to four times per year.
This role is accountable for:
• Ensuring the accuracy, usefulness, reliability, and accessibility of our data products
• Defining and setting priorities and roadmaps for Data Platform Engineering teams across four domains: data engineering, search, experimentation, and site reliability
• Product lifecycle management of the products, services, and tools of the Data Platform Engineering teams
• Co-developing product strategy, providing leadership, and making and facilitating sound decisions
• Managing and developing a team of product managers
• Partnering with user-facing product teams to use the data platform to guide product decisions and build derived-data products
Expected skills and experience include:
• Minimum of 5 years of product management experience with data or infrastructure products
• Experience hiring and managing product managers
• Success delivering data and analytical products and services depended on by multiple product teams
• Expertise in data analytics, A/B testing, search, and data architecture
• Strong understanding of modern techniques for handling high-scale data
• Knowledge of search technologies
• Experience navigating privacy issues around data collection, retention, and distribution
• Ability to work with multiple stakeholder teams to deliver results through lateral influence and collaboration
Qualities that are important to us:
• Commitment to the mission and values of the Wikimedia Foundation
• Effective at asynchronous communication in a distributed workplace
• Able to navigate and make decisions in circumstances with limited, incomplete, and conflicting information
• Focus on iterative delivery and minimum viability to provide value to customer teams
• Effective at clear, written communication for strategy, plans, roadmaps, and decisions, for a wide range of audiences including individual contributor engineers, volunteer contributors, and department leader
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