Senior Data Engineer - Data Ingestion, Enrichment

Preply

Senior Data Engineer in Data Ingestion and Enrichment team at Preply. Responsible for building and managing data lakes and ingestion pipelines to support analytics and ML.

Posted 7/21/2026full-timeLondon • 🇬🇧 United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable data ingestion pipelines and architectures, with a strong focus on data quality, observability, and cross-functional collaboration. Proficient in utilizing cloud platforms and orchestration tools to enhance data processing capabilities.

Highest-signal resume keywords

Data Lake DesignBatch And Streaming Ingestion PipelinesReal-Time Data ProcessingCloud Platforms (AWS/GCP)Orchestration Tools (Airflow, dbt)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData Quality MetricsData ContractsData StandardizationArchitectural PatternsHigh-Volume Data PipelinesEfficient AlgorithmsReal-Time ProcessingBatch ProcessingData Engineering

Soft Skills

Problem-SolvingProactive MindsetInnovative ThinkingCommunicationCross-Functional Collaboration

Tools & Technologies

SparkFlinkKafkaDebeziumAirflowDbt

Industry Keywords

Data EngineeringDevOps PracticesData PrivacyAccess ControlData Classification

Tech Stack

Tools & technologies

AirflowAWSCloudGoogle Cloud PlatformKafkaSpark

About the role

Key responsibilities & impact

Design, build, and own Preply’s data lake.
Develop and operate scalable, reliable batch and streaming ingestion pipelines.
Define and implement data contracts between producers and consumers.
Build enrichment logic that joins, standardizes, and contextualizes data across domains.
Instrument ingestion pipelines with strong observability: freshness, latency, data quality, and cost metrics.
Apply consistent access control, classification, and privacy protections at ingestion time.
Contribute to standardized ingestion templates, shared libraries, and platform tooling that enable teams to onboard new data sources independently.
Work closely with Product, Backend, Analytics, and ML partners to align on ingestion requirements.

Requirements

What you’ll need

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+)

Benefits

Comp & perks

A generous monthly allowance for lessons on __Preply.com__
Learning & Development budget
Time off for your self-development
A competitive financial package with equity
Leave allowance
Health insurance
Access to free mental health support platforms