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Preply is a unicorn edtech platform (Series D, $150M) that connects 100,000+ tutors teaching 90+ languages to learners across 180 countries. The company is building human-led, AI-enhanced learning experiences at global scale.
The Data Platform team provides the foundational data infrastructure for all analytics, machine learning, and product features across Preply. The team owns end-to-end batch and streaming ingestion pipelines, data contracts, quality checks, data modeling, governance, and self-service tooling that enables other teams to onboard new data sources safely. The platform serves as a critical dependency for Analytics Engineering, Data Science, ML Platform, Backend, and Product teams.
As Senior Engineering Manager for Data Platform, you will lead and grow a high-performing data engineering team while owning the long-term technical strategy and execution of Preply's data foundation (the Lakehouse, ingestion layers, data contracts, enrichment, and governance). You'll coach and develop senior engineers, define career paths, and foster a culture of ownership and technical excellence. You'll partner closely with Analytics, ML Platform, Data Science, and Product leaders to identify high-impact opportunities and ensure the team focuses on datasets, pipelines, and tooling that deliver the greatest customer and business value.
Key responsibilities include: translating data platform strategy into realistic execution plans; providing technical leadership on architecture decisions across batch/streaming ingestion, data modeling, quality, and governance; establishing SLOs and observability to move from reactive firefighting to proactive reliability; championing engineering best practices and continuous improvement; collaborating cross-functionally to align on data ownership and standards; and owning hiring, team composition, and operating model evolution.
Preply has achieved 90%+ adoption of AI coding tools across engineering and is moving toward more autonomous, AI-augmented development at scale. You'll help your team adopt these ways of working while setting appropriate standards and guardrails.
QUALIFICATIONS:
- 8+ years of software or data engineering experience, including 5+ years in engineering management
- Demonstrated experience leading data or platform engineering teams
- People-centric approach with proven track record of hiring, coaching, and retaining high-performing teams, including senior engineers
- Strong technical judgment and systems thinking; comfort driving architectural discussions and evaluating technical trade-offs
- Product and business partnership skills; ability to work closely with Analytics, Data Science, ML, and Product partners to identify opportunities and drive measurable outcomes
- Clear communication and stakeholder leadership; ability to align teams with different incentives and make sound decisions with incomplete information
- Results-oriented with track record of driving performance and motivating teams to achieve ambitious, business-focused goals
- Ethical leadership approach demonstrating empathy, transparency, accountability, and strong ownership
NICE TO HAVE:
- Hands-on familiarity with modern data stack (Spark, Flink, Kafka, Debezium, Airflow, dbt, or similar)
- Experience with cloud platforms (AWS/GCP) 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)
- Experience with data governance, privacy, and compliance at ingestion time
- Familiarity with feature stores, ML data pipelines, or preparing data for GenAI/RAG use cases
- AI expertise using Agentic AI beyond code generation for architecture, planning, and decision-making while retaining human judgment for critical decisions
