Senior Data Engineer

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.

   

  Skills Required:

• 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.