Informacje o stanowisku

Are you ready to design cutting-edge data solutions, drive cloud migrations, and work with AI technologies? Our client is looking for a skilled Snowflake Data Engineer to help shape the future of data-driven decision-making. If you thrive on innovation, scalability, and collaboration—this is the opportunity for you!

What we expect

• At least 3 years of experience in Big Data or Cloud projects focused on processing and visualizing large or unstructured datasets, including at least 1 year of hands-on experience with Snowflake.
• Understanding of Snowflakes pricing model and experience in applying cost optimization strategies for efficient resource management.
• Experience in designing and implementing data transformation pipelines natively in Snowflake or through Service Partners.
• Familiarity with Snowflake’s security model and best practices.
• Practical experience with at least one public cloud platform in areas such as Storage, Compute (including Serverless), Networking, and DevOps.
• Basic proficiency in SQL and at least one programming language, such as Python, Scala, Java, or Bash.
• Very good command of English.

Employment agency entry number 47

this job offer is intended for people over 18 years of age

What we offer

• Permanent employment contract from day one.
• Hybrid and flexible working model.
• Comprehensive home office equipment package.
• Private medical care through Medicover.
• Life insurance.
• Access to the NAIS benefits platform.
• Over 70 training tracks with certification opportunities.
• Free access to platforms like Pluralsight, TED Talks, Coursera, Udemy Business, and SAP Learning Hub.
• Access to over 20 professional communities, including Salesforce, Java, Cloud, IoT, Agile, and AI, where you can network and grow with like-minded professionals.

Your tasks

• Design, develop, and maintain Snowflake data pipelines to support various business functions.
• Collaborate with cross-functional teams to gather data requirements and implement scalable, efficient solutions.
• Optimize data models and schemas to ensure high performance and efficiency.
• Ensure data integrity, quality, and security throughout the entire data lifecycle.
• Implement monitoring and alerting systems to proactively detect and resolve issues.
• Plan and execute the migration of on-premises data warehouses to Snowflake.
• Develop solutions leveraging AI, ML, and Generative AI technologies.
• Stay current with Snowflake best practices and emerging technologies to drive continuous improvement.

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