Data ETL Engineer

O projekcie: Location Requirements Hybrid from Kraków, 2 days per week in the office 8-10 months or longer contract Wymagania: Must have: - 3+ years of experience in SQL development and query optimization, particularly in BigQuery environments. - Experience designing and implementing ETL/ELT pipelines and data transformation processes. - Hands-on experience with GCP data services such as BigQuery, Data Fusion, Cloud Composer/Airflow, or similar tools. - Practical experience with Data Vault modeling. - Programming experience in Python and familiarity with Terraform. - Experience with CI/CD pipelines and DevOps tools (e.g., Git, Jenkins, Ansible). - Experience working in Agile environments and DataOps practices. - Strong analytical and problem-solving skills. - Important: The client requires a visit to Kraków for two days each month. Nice to have: - Experience designing data ingestion pipelines for formats such as CSV, JSON, and XML. - Experience integrating data from REST or SOAP APIs, SFTP servers, and enterprise data sources. - Knowledge of data contract best practices. - Experience with Java development or building custom plugins for data integration tools. - Experience with continuous testing and delivery for cloud-based data platforms. - Strong communication and collaboration skills. - Ability to work independently and manage multiple tasks. - Proactive mindset with a strong problem-solving approach. - Willingness to learn and continuously improve technical skills. - Team-oriented attitude and ability to work effectively in cross-functional teams. Required Technical Skills - SQL - BigQuery - ETL & Data Management Tools - CI/CD - Python - Terraform - Agile Codzienne zadania: - Design, build, test, and deploy data models and transformations in BigQuery using SQL and related technologies. - Develop and maintain ETL/ELT pipelines to transform raw and unstructured data into structured datasets using Data Vault modeling. - Integrate data from multiple sources, including on-premise systems, APIs, and cloud-based platforms. - Monitor and troubleshoot data pipelines for performance issues, failures, or data inconsistencies. - Optimize ETL/ELT processes for performance, scalability, and cost efficiency. - Review and implement business and technical requirements in data transformation processes. - Ensure solutions meet non-functional requirements, including security, reliability, scalability, and compliance with IT standards. - Manage code repositories and CI/CD pipelines using tools such as Git and Jenkins. - Collaborate with DevOps and data teams to enable automated deployment, testing, and monitoring. - Provide bug fixes, enhancements, and technical documentation, and support knowledge transfer to operational teams.