Engineering Manager (Data Platform)

We power people’s progress.

At Preply, we’re all about creating life-changing learning experiences. We help people discover the magic of the perfect tutor, craft a personalised learning journey, and stay motivated to keep growing. Our approach is human-led, tech-enabled - and it’s creating real impact.

We’ve just reached unicorn status with a $150M Series D, accelerating our vision to transform education through human-led, AI-enhanced learning. Today, 100,000+ tutors teach 90+ languages to learners in 180 countries - and we’re only getting started. As a category-defining company, we’re shaping what the future of learning looks like at global scale.

Every Preply lesson sparks change, fuels ambition, and drives progress that matters. Joining Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day.

Meet the team!

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, forming a durable data moat for AI-driven products.

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. It works closely with ML Platform, Applied and Data Scientists, Analytics Engineering, Backend, and Product squads, so that datasets, features, and pipelines are production-ready, observable, and reusable across Preply.

As the Senior Engineering Manager for Data Platform, you'll own the engineering strategy, execution, and organizational health of the team that every analytics, ML, and AI initiative at Preply depends on. This is a leadership role for a manager with strong technical judgment. You'll go deep on data architecture, reliability, and platform abstractions, coach senior engineers, set operational standards, and partner with Data, ML, Product, Security, and Engineering leaders across the company.

We've reached 90%+ adoption of AI coding tools across engineering, and are now moving towards more autonomous, AI-augmented development at scale. As an Engineering Manager, you’ll help your team adopt these ways of working while setting the right standards and guardrails.

Learn more about how we build on our Engineering Blog, Tech Radar, and YouTube channel!

Our Principles

• 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. You know how to create alignment, foster psychological safety, provide actionable feedback, and develop engineers through coaching and mentorship.
• Strong technical judgment and systems thinking. You are 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: You're comfortable working closely with Analytics, Data Science, ML, and Product partners to identify opportunities, prioritize investments, and drive measurable outcomes. You naturally connect data platform decisions to downstream user experience, business metrics, and company strategy.
• 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. You know how to motivate teams to set and achieve ambitious, business-focused, and measurable goals.
• Ethical Leadership: You lead by example, serving as the team's moral compass by demonstrating empathy, transparency, accountability, and a strong sense of ownership. You value honesty and fairness, creating a culture where people feel safe to challenge ideas, learn, and grow.
• 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: You use Agentic AI beyond code generation to support architecture, planning, and decision-making, while retaining human judgment for architecture, people decisions, business logic, and security, and establishing quality gates and safety nets for team workflows.