Senior Engineering Manager (Data Platform)

At Preply, the Data Platform team provides a single, trusted, and scalable data foundation for the whole company. The team ensures that all analytics, machine learning, and product features are built on unified, governed, and production-grade data assets in Preply's Lakehouse, including the extraction, normalization, and generation of structured data from Preply's unstructured assets. The team owns end-to-end batch and streaming ingestion pipelines, data contracts and quality checks, enrichment and modeling across domains, and the self-service tooling that lets other teams onboard new data sources within clear guardrails. As the Senior Engineering Manager for Data Platform, you'll own the engineering strategy, execution, and organizational health of the team. This is a leadership role for a manager with strong technical judgment.

Responsibilities

Lead and grow a high-performing data engineering team, fostering a culture of ownership, continuous improvement, and technical excellence; Coach and develop engineers through regular feedback, mentorship, and career development, while creating an inclusive and collaborative team environment; Define and drive the long-term vision for Preply's data foundation (the Lakehouse, ingestion layers, data contracts, enrichment, and governance), ensuring alignment with company objectives and the needs of analytics, ML, and product teams; Identify and prioritize high-impact opportunities, partnering with Analytics, ML Platform, Data Science, and Product; Own execution and delivery, translating strategy into realistic plans while balancing platform investment with near-term needs and maintaining speed, quality, cost efficiency, and predictability; Provide technical leadership, guiding architecture across batch and streaming ingestion, data modeling, quality, and governance; Own data reliability and trust by establishing SLOs, observability, and incident response for data pipelines; Champion engineering best practices, driving continuous improvements in code quality, operational excellence, development processes, and technology evolution; Collaborate cross-functionally with stakeholders across the business to align on priorities, data ownership, standards, and outcomes; Own hiring quality, team composition, and operating model, evolving team boundaries as the platform and company needs change

Requirements

8+ years of software or data engineering experience, including 5+ years in engineering management, with experience leading data or platform engineering teams; People-centric approach and team-building skills: a passion for building high-performing teams and helping people grow; Strong technical judgment and systems thinking, comfortable driving architectural discussions, evaluating technical trade-offs, championing engineering best practices, and partnering with senior engineers on technical strategy; A track record of hiring, coaching, and retaining high-performing teams, including senior engineers; Product & Business Partnership: comfortable working closely with Analytics, Data Science, ML, and Product partners to identify opportunities, prioritize investments, and drive measurable outcomes; Clear communication and stakeholder leadership, with the ability to align teams with different incentives, make sound decisions with incomplete information, and revisit assumptions as the data ecosystem changes; Results-Oriented: a track record of driving performance and motivating teams to set and achieve ambitious, business-focused, and measurable goals; Ethical Leadership: leads by example, demonstrating empathy, transparency, accountability, and a strong sense of ownership, valuing honesty and fairness

Nice to have

Hands-on familiarity with the modern data stack, for example Spark, Flink, Kafka, Debezium, Airflow, dbt, or similar, and with cloud platforms (AWS/GCP or equivalent) and modern DevOps practices; Experience leading teams that built data platforms used by multiple teams in fast-growing companies; Experience running a data platform as a product: data contracts, self-service onboarding, discoverability, and measuring success through adoption and consumer outcomes; Experience with data governance, privacy, and compliance at ingestion time (classification, access control, masking, auditability); Familiarity with feature stores, ML data pipelines, or preparing data for GenAI / RAG use cases; AI Expertise: uses Agentic AI beyond code generation to support architecture, planning, and decision-making, while retaining human judgment and establishing quality gates and safety nets for team workflows

Benefits

A generous monthly allowance for lessons on Preply.com; Learning & Development budget and time off for self-development; A competitive financial package with equity, leave allowance and health insurance; Relocation package for candidates not in Barcelona joining the Preply Barcelona Hub; Access to free mental health support platforms; Access to Gympass-partnered wellness and gym centers throughout Spain; An open, collaborative, dynamic, and diverse culture