We’d like you to:

• Ship safely and incrementally. Drive the work across data engineering, search, experimentation, and data SRE in close partnership with product management to align technical execution with user needs and priorities. Balance velocity with reliability, involving stakeholders both inside Wikimedia and the larger volunteer community. 
• Develop people and teams. Manage managers, coach senior ICs, scale hiring for a diverse, international, remote-first organization, and foster a collaborative, mission-aligned culture.
• Provide technical strategy and oversight. Set architectural direction grounded in experience with event-based architectures, data ingestion, modeling, freshness/accuracy SLOs, data governance, privacy by design principles, and cost efficiency.
• Partner effectively with Product Management. Collaborate with our Group Product Manager for Data Platform and senior PMs to balance technical implementation with diverse user needs. Navigate priority trade-offs through healthy debate and shared accountability.
• Be an operational multiplier. Identify and share patterns across teams that reduce toil and let ICs focus on what they do best.

You are:

• Deeply technical with strong judgment. You can read design docs and PRs, spot missing edge cases or constraints, and make calls grounded in industry best practice.
• Biased towards shipping regularly and with confidence. You break work into safe, incremental releases with a crisp definition of done, unblock teams quickly, and measure outcomes.
• Operationally focused. You set and hold SLOs/error budgets, collaborate with stakeholders, manage vendor relationships, and treat incidents as opportunities to automate and harden systems.
• Collaborative across functions. You build strong partnerships with product management, research, analytics, and product teams to achieve shared outcomes.
• Mission driven. You balance product impact with privacy and transparency, partnering with volunteers to build in the open for a global, multilingual community.

Skills and Experience:

• 8+ years of engineering leadership with 3+ years managing managers across data-heavy backend teams (or an equivalent track record of shipping production data systems at internet scale).
• Track record of shipping production data systems at massive scale.
• Hands-on experience with relevant open source tech stacks (e.g. Kubernetes, Kafka, Spark, Flink, Hadoop, Ceph, Airflow).
• Ability to hire, coach, and lead globally distributed teams.