Senior Data Engineer Europe

Our client is a global jewelry manufacturer undergoing a major transformation, moving from IaaS-based solutions to a modern Azure PaaS data platform. As part of this journey, you will design and implement scalable, reusable, and high-quality data products using technologies such as Data Factory, Data Lake, Synapse, and Databricks. These solutions will enable advanced analytics, reporting, and data-driven decision-making across the organization.

By collaborating with product owners, architects, and business stakeholders, you will play a key role in maximizing the value of data and driving measurable commercial impact worldwide.

Design, develop, and maintain scalable ETL processes and data pipelines.

Collaborate with product owners, architects, and cross-functional teams to translate business and product requirements into technical solutions.

Ingest, transform, and optimize large, complex data sets while ensuring data quality, reliability, and performance.

Ensure data integrity, quality, and consistency through rigorous testing and validation.

Optimize data storage, retrieval, and processing for performance and scalability.

Apply Dev Ops practices, CI/CD pipelines, and coding best practices to ensure robust, production-ready solutions.

Document technical specifications, data models, and system architecture for team alignment and long-term maintainability.

Contribute to a culture of innovation by following best practices while exploring new ways to push the boundaries of data engineering.

5+ years of experience as a Data Engineer, with a strong track record of designing, building, and delivering production-ready data products at enterprise scale.

Proficiency in Python, SQL, and relevant programming languages.

Production experience with Azure Synapse Analytics, Databricks, and PySpark.

Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform).

Solid understanding of ETL processes, data warehousing, and database management (Postgre

SQL, MySQL, Mongo

DB, etc.).

Ability to design and implement data models for transactional and analytical systems.

Strong analytical thinking and problem-solving skills.

Excellent communication skills to work effectively in cross-functional teams.

Attention to detail, adaptability, and a collaborative mindset.

Leadership or mentoring experience is a plus.