Preply
Education
SeniorIIDataEngineerDataIngestionandEnrichmentteam
“Senior II Data Engineer - Data Ingestion and Enrichment team at Preply. Skills: Data Ingestion, Data Enrichment, Data Lake, Data Pipelines, Data Quality, Observability, Cloud Platforms, Orchestration Tools. Design, build, and own Preply’s data lake.. Ensure every dataset has clear ownership, purpose, schemas, and quality expectations.”
What You'll Achieve.
Build trusted ingestion & enrichment foundations (Data Lake and Data as a Product); Ensure every dataset has clear ownership, purpose, schemas, and quality expectations from first ingestion through downstream consumption.; Treat trust, correctness, and predictability as first-class features of the platform.; Develop and operate scalable, reliable batch and streaming ingestion pipelines that support both real-time and analytical use cases.; 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.; Support historical tracking, point-in-time correctness, and dataset versioning so downstream users can confidently analyze changes and impacts over time.; 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.; 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.; Improve discoverability, documentation, and metadata so datasets are easy to find, understand, and trust without relying on tribal knowledge.
Industry & Context.
Exceptional problem-solving skills; Dive deep; Investigate disparities between numbers and stories, unlocking meaningful insights to guide our decisions.
What They're Looking For.
Must Have
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., communication and cross-functional collaboration skills (English level B2+)
Nice to Have
Proven track record in scaling data infrastructures within fast-growing startups, Terraform/Kubernetes for data tooling, SQL proficiency
What You'll Do.
and own Preply’s data lake.
Ensure every dataset has clear ownership
and quality expectations.
Develop and operate scalable
reliable batch and streaming ingestion pipelines.
Design clear raw → standardized → consumption layers.
Define and implement data contracts between producers and consumers.
and quality checks early in the ingestion lifecycle.
Build enrichment logic that joins
and contextualizes data across domains.
Support historical tracking
point-in-time correctness
and dataset versioning.
Instrument ingestion pipelines with observability: freshness
and incident response playbooks.
Apply consistent access control
and privacy protections at ingestion time.
Contribute to standardized ingestion templates
and platform tooling.
Improve discoverability
and metadata so datasets are easy to find
How You'll Work.
Team & Collaboration
Work closely with ML Platform, Applied/Data Scientists, Analytics Engineering, and Product squads.; Drive cross-functional initiatives involving stakeholders from different functional areas and different levels of seniority.; Work closely with Product, Backend, Analytics, and ML partners to align on ingestion requirements, trade-offs, and priorities.; Promote shared ownership of data quality and platform standards.; Foster a culture where teams move fast together under common data contracts and principles.; Prioritize collaboration, inclusion, and the success of our team over personal ambitions.; Support and celebrate each other's progress.
Communication Scope
English level B2+
Process & Methodology
Leading multi-stakeholder deliveries
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