Must have

• AWS

• ETL

• Snowflake

• data vault

• Docker

• Python

• SQL

• Unix

• Polish (C1)

• English (C1)

Requirements description

• Strong expertise in cloud technologies and the Snowflake ecosystem, particularly AWS, Data One Platform, Immuta, Collibra, and cloud security aspects
• Minimum 5 years of experience in Python programming for building and maintaining data pipelines
• Advanced knowledge of databases, including query optimization, relational schema design, and MPP using SQL
• Expertise in data storage technologies, including files, relational databases, MPP, NoSQL, and various data types (structured, unstructured, metrics, logs)
• Deep familiarity with Data Vault, Data Mesh, dimensional modeling, and metadata management
• Understanding of business and analytical processes, as well as integration with analytics and reporting systems
• Experience working in Agile environments, coaching development teams with the use of fluent English and Polish
• Residing in Poland required

Nice-to-have requirements

• Knowledge of Pharma data formats is a big plus

Offer description

We are looking for a Data Engineer with expertise in Snowflake, AWS, and ETL processes, who will work closely with AI scientists and data analysts to design, develop, and maintain data pipelines and systems that support clinical and operational data use cases.

Your responsibilities

1. Design and develop data architecture incorporating Snowflake, Immuta, Collibra, and cloud security
2. Implement and optimize ETL/ELT processes, manage raw data, automate workflows, and ensure high performance and reliability of data processing systems
3. Manage data quality and security, monitor quality, and implement metadata management strategies
4. Collaborate with analytics and business teams to identify user needs and deliver comprehensive solutions supporting analytics and reporting
5. Optimize and migrate data systems through data and process conversion from existing systems to Data Vault
6. Define and enforce coding standards, data modeling, and ETL/ELT architecture, ensure compliance with Data Mesh and other modern approaches

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