Data Platform Engineering Manager

Euromonitor International

HybridPosted 4 августа 2026 г.

About the role

Vilnius, Lithuania – Hybrid work arrangement. The Data Platform Engineering Manager leads data platform engineering teams distributed globally, delivering reliable, data-centric solutions including data systems, pipelines, and data manipulations. This is a people-first leadership role with strong technical accountability: setting direction, removing blockers, and ensuring the team delivers high-quality data services. The Manager partners closely with Team Leaders to build a healthy, inclusive, and high-performing culture grounded in trust and psychological safety, while hiring, coaching and developing engineers and leaders through regular 1:1s, feedback, and performance reviews.

Data Platform Engineering Manager

Euromonitor International

HybridPosted 4 августа 2026 г.

About the role

Vilnius, Lithuania – Hybrid work arrangement. The Data Platform Engineering Manager leads data platform engineering teams distributed globally, delivering reliable, data-centric solutions including data systems, pipelines, and data manipulations. This is a people-first leadership role with strong technical accountability: setting direction, removing blockers, and ensuring the team delivers high-quality data services. The Manager partners closely with Team Leaders to build a healthy, inclusive, and high-performing culture grounded in trust and psychological safety, while hiring, coaching and developing engineers and leaders through regular 1:1s, feedback, and performance reviews.

Key responsibilities: - People Leadership & Team Health: Hire, coach and develop engineers and Team Leaders; foster an inclusive, psychologically safe culture; maintain sustainable pace and team morale; actively remove blockers so the team can deliver. - Delivery, Backlog & Stakeholder Alignment: Own and prioritise the backlog and roadmap for data platform services/capabilities; align stakeholders and external teams on outcomes, scope and timelines; manage dependencies, risks and delivery plans; communicate clearly why and what to the team; ensure services are production-ready (SLAs/SLOs, release and change practices). - Continuous Improvement: Drive continuous improvement based on data and feedback; identify and remove sources of toil and delivery friction; improve data platform experience for external teams through automation, standardisation and self-service capabilities. - Strategy & Outcomes:

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