Senior Data Engineer - Zalando Turkey

Zoolatech; Fatih; In loco; TRY 400.000 - 800.000; Tempo pieno

Descrizione del lavoro

Zoolatech is seeking a Senior Data Engineer in Turkey to design scalable pipelines that reconcile customer identifiers from web, app, CRM, and marketing channels. You will build identity mapping, lead AI-assisted data cleanup, and enforce GDPR-compliant privacy and data retention from day one.

You’ll collaborate with backend engineers and analysts, contribute to data contracts, and help shape a new data team with modern tooling and standards.

Competenze

• 5+ years as a Data Engineer or 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 modelling, data quality and large-scale distributed data processing.
• Practical experience using AI/LLM tools to automate data engineering tasks.
• Experience with event streaming (Kafka or similar).
• Upper-Intermediate English or higher.

Mansioni

• Design and build scalable pipelines that ingest, normalise 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.

Conoscenze

PySpark

SQL

Databricks

Airflow

Data modelling

Data quality

AI/LLM tools

Kafka

Strumenti

Spark ecosystem

Descrizione del lavoro

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, personalisation 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, normalise 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 modelling, 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 (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)

Experience in e-commerce or retail tracking/analytics