Senior Data Engineer Central Europe

Overview

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.

Responsibilities

Design, build, and maintain scalable, efficient, and reusable data pipelines and products on the Azure PaaS data platform.

Collaborate with product owners, architects, and business stakeholders to translate requirements into technical designs and data models.

Enable advanced analytics, reporting, and other data-driven use cases that support commercial initiatives and operational efficiencies.

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

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

Monitor and own the stability of delivered data products, ensuring continuous improvements and measurable business benefits.

Promote a "build-once, consume-many" approach to maximize reuse and value creation across business verticals.

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

Must-Have Skills

5+ years of experience as a Data Engineer with proven expertise in Azure Synapse Analytics and SQL Server

Advanced proficiency in SQL , covering relational databases, data warehousing, dimensional modeling, and cubes.

Practical experience with Azure Data Factory, Databricks, and PySpark

Track record of designing, building, and delivering production-ready data products at enterprise scale.

Strong analytical skills and ability to translate business requirements into technical solutions.

Excellent communication skills in English, with the ability to adapt technical details for different audiences.

Experience working in Agile / Scrum teams.

Nice-to-Have Skills

Familiarity with infrastructure tools such as Kubernetes and Helm.

Experience with Kafka.

Experience with DevOps and CI / CD pipelines.

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