Locuri de muncă în Bucharest, romania, romania
Ultima actualizare: acum 11 zile
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Senior Data Engineer
Digital PiplBucharest, Bucuresti, RomaniaÎn urmă cu peste 30 de zile
Descrierea postuluiLead the integration, processing, and transformation of data within the Snowflake environment, ensuring seamless operation across the data pipeline. Oversee the entire data integration lifecycle, from ingestion to curated datasets, enabling data analysts and other stakeholders to access reliable and actionable data. Ensure the timeliness, accuracy, quality, and completeness of data products to meet business and stakeholder requirements. Drive the design and development of robust and scalable data assets within Snowflake to support current and future business needs. Partner with cross-functional teams to conceptualize and implement an event-driven target architecture that aligns with organizational goals. Actively participate in use-case-driven teamwork to create and continuously enhance data products, adhering to agile principles and practices. Maintain clear, detailed, and up-to-date documentation of processes, workflows, and developments in Confluence and Jira. Continuously explore and implement new tools, techniques, and best practices to optimize data integration processes and enhance team efficiency. Bachelor's degree in (Business) Computer Science, Mathematics, or a related field. Advanced knowledge of DBT, SQL, and Python, including an understanding of their limitations and the ability to identify when to use alternative tools or programming languages. Expertise in DWH / Lakehouse architectures, BI / Analytics best practices, and experience working in cloud environments such as Snowflake and Azure Data Factory. Proficiency with collaboration tools like Confluence and Jira. Strong analytical thinking, coupled with a structured and goal-oriented working approach. Excellent interpersonal, written, and verbal communication skills in both German and English. A collaborative and enthusiastic team player with a high level of motivation. High affinity for numbers, demonstrating strong analytical capabilities and strategic thinking. Fluency in English, both written and spoken.
About the Client
Our client is a leading global supplier of high-quality products for the modern kitchen-living room based in Germany. For over 285 years, our client has offered premium products that enhance the lives of professional and home chefs worldwide. Since its start as an esteemed cutlery brand, the company has grown to include a coveted collection of cookware, flatware, glassware, and kitchen gadgets. Tradition, quality, innovation, and craftsmanship are their ingredients for success.
Today, Our client is an international industry leader that sells products in 100 countries. As a company and the employer, our client is characterized by strong innovative strength, entrepreneurial foresight, global work, and respectful interaction with one another. Outstanding quality, excellent design, and exceptional durability - these are the demands of their products.
Project details
The project focuses on building and optimizing a robust, cloud-based data ecosystem leveraging Snowflake and Azure Data Factory. It involves designing scalable data architectures, integrating and processing data from ingestion to curation, and delivering high-quality, analytics-ready datasets. The team adopts agile methodologies to drive continuous improvement, ensure data accuracy and timeliness, and support business intelligence and analytics initiatives.
Your Team
You will become part of a highly skilled and experienced data analytics team dedicated to leveraging cutting-edge technologies and best practices to deliver high-quality data solutions.
What's in it for you
- Interview process that respects people and their time
- Professional and open IT community
- Internal meet-ups and resources for knowledge sharing
- Time for recovery and relaxation
- Bright online and offline events
- Opportunity to become part of our internal volunteer community
Responsibilities
Skills
Proven professional experience in data engineering, with a strong foundation in data modeling and structuring.