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Senior Data Engineer

Zoolatech·Salary not specified

Primary stack

SQLDatabricksAirflowApache Spark

Nice to have's

ScalaAWSE-commerce

Job description

About the Position

Together with our partner, a leading European online fashion & beauty retailer, we’re looking for a Senior Data Engineer to join a new initiative focused on customer identity and data interoperability. Customers interact with the platform across web, app, CRM, and marketing channels, and each system identifies them differently. You’ll help design and build the data foundation that connects and reconciles these identifiers. This enables reliable customer journey analytics, personalization, and privacy-compliant data usage at scale.

Part of the role is applying AI to the data itself. You’ll use LLM-based tooling and automation to speed up repetitive work such as data cleanup, deduplication, anomaly detection, and data quality validation across large customer datasets.

Responsibilities

  • Design and build scalable pipelines that ingest, normalize, and reconcile customer identifiers from multiple sources
  • Develop identity mapping and stitching logic, for example anonymous-to-logged-in and cross-device
  • Lead data cleanup and migration of legacy identifier data, using AI-assisted automation to reduce manual effort
  • Define and implement data quality checks, validation rules, and monitoring for identity data
  • Build in privacy, consent, and data retention requirements (GDPR) from the start
  • Work closely with backend engineers, analysts, and data consumers to define data contracts and downstream usability
  • Contribute to technical design, documentation, and engineering standards in a newly forming team

Requirements

Must-have:

  • 5+ years of experience as a Data Engineer or in a similar role
  • Strong hands-on experience with PySpark/Apache Spark and SQL
  • Production experience with Databricks or similar systems
  • Experience with pipeline orchestration (e.g. Airflow)
  • Solid understanding of data modeling, data quality, and large-scale distributed data processing
  • Practical experience using AI/LLM tools to automate data engineering tasks, such as cleanup, classification, validation, or code generation
  • Experience with event streaming (e.g. Kafka or similar)
  • Upper-Intermediate English or higher

Nice-to-have:

  • Experience with identity resolution, customer data platforms (CDP), or master data management
  • Experience with privacy-sensitive data (pseudonymisation, hashing, consent management)
  • Java/Kotlin or Scala, plus AWS data services
  • Experience in e-commerce or retail tracking/analytics

We Offer

  • Paid Vacation
  • Sick Days
  • Sport/Insurance Compensation
  • English Classes
  • Charity
  • Training Compensation

About the Company

[Company description if present]

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