Technical Requirements

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

Main Responsibilities

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.

Location Requirements

Hybrid from Kraków, 2 days per week in the office

8-10 months or longer contract

Data ETL Engineer

Crestt