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.

• 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 DevOps 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.

• 3-5 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.

• Practical 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 (PostgreSQL, MySQL, MongoDB, 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.

Benefits:

• Paid Vacation
• Hybrid Work (home/office)
• Sick Days
• Sport/Insurance Compensation
• Holidays Day Off
• English Classes
• Training Compensation
• Transportation compensation