Senior Data Engineer

Навыки

• Airflow
• AWS
• Data Lake
• Data Quality
• dbt
• Flink
• Форензика и реагирование

О компании и продукте

• Care to change the world - We are passionate about our work and care deeply about its impact to be life changing.
• We do it for learners - For both Preply and tutors, learners are why we do what we do. Every day we focus on empowering tutors to deliver an exceptional learning experience.
• Keep perfecting - To create an outstanding customer experience, we focus on simplicity, smoothness, and enjoyment, continually perfecting it as every detail matters.
• Now is the time - In a fast-paced world, it matters how quickly we act. Now is the time to make great things happen.

Задачи

• Build trusted ingestion & enrichment foundations (Data Lake and Data as a Product)
• Design, build, and own Preply’s data lake
• Ensure every dataset has clear ownership, purpose, schemas, and quality expectations from first ingestion through downstream consumption by analytics, product, and ML teams
• Treat trust, correctness, and predictability as first-class features of the platform
• Own end-to-end ingestion pipelines (batch & streaming)
• Develop and operate scalable, reliable batch and streaming ingestion pipelines that support both real-time and analytical use cases. Design clear raw
• standardized
• consumption layers with explicit responsibilities, lineage, and retention strategies. Balance performance, cost, and reliability as the platform scales
• Data quality, contracts & early validation
• Define and implement data contracts between producers and consumers, covering schema, freshness, volume, and quality guarantees
• Embed validation, anomaly detection, and quality checks early in the ingestion lifecycle to catch issues before they propagate
• Standardize how quality metrics are measured, monitored, and surfaced across the platform
• Enrichment, modeling & lifecycle management
• Build enrichment logic that joins, standardizes, and contextualizes data across domains using shared definitions and reusable patterns
• Support historical tracking, point-in-time correctness, and dataset versioning so downstream users can confidently analyze changes and impacts over time
• Observability, reliability & operational excellence
• Instrument ingestion pipelines with strong observability: freshness, latency, data quality, and cost metrics
• Contribute to SLOs, alerting, and incident response playbooks so data failures are visible, diagnosable, and recoverable
• Help move the platform from reactive firefighting to proactive reliability management
• Governance & compliance by design
• Ensure sensitive data is properly masked, minimized, or anonymized by default, and that all data flows are auditable and traceable
• Make governance invisible to users but deeply embedded in platform workflows
• Enable self-service & standardization
• Contribute to standardized ingestion templates, shared libraries, and platform tooling that enable teams to onboard new data sources independently within clear guardrails
• Improve discoverability, documentation, and metadata so datasets are easy to find, understand, and trust without relying on tribal knowledge

Требования

• Exposure to and experience building architectural patterns of a large, high-scale application (e.g., well-designed APIs, high-volume data pipelines, efficient algorithms)
• Solid experience working in platform or data engineering teams (or equivalent impact) with evidence of leading multi-stakeholder deliveries
• Familiarity with cloud platforms (AWS/GCP or equivalent) and modern DevOps practices
• Hands-on experience designing and implementing real-time and batch data processing infrastructures using modern frameworks like Spark, Flink, Spark streaming, Kafka, Debezium, etc
• Expertise with orchestration tools such as Airflow, dbt, or similar
• Exceptional problem-solving skills paired with a proactive, innovative mindset focused on continuous improvement
• Strong communication and cross-functional collaboration skills (English level B2+)
• This role combines hands-on engineering with technical leadership

Условия

• An open, collaborative, dynamic, and diverse culture
• A generous monthly allowance for lessons on http://preply.comPreply.com http://Preply.com, Learning & Development budget, and time off for your self-development
• A competitive financial package with equity, leave allowance, and health insurance
• Access to free mental health support platforms
• The opportunity to unlock the potential of learners and tutors through language learning and teaching in 175 countries (and counting!)
• 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 ingestion and enrichment team provides a single, trusted, and scalable data foundation
• The team ensures that all analytics, machine learning, and product features are built on unified, governed, and production-grade data assets in Preply’s Lake House, including the extraction, normalization, and generation of structured data from Preply’s unstructured assets, forming a durable data moat for AI-driven products

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