This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
We are seeking a Mid-Level Enterprise Data Warehouse (EDW) Engineer with a passion for building scalable, cloud-native data solutions. This position is ideal for individuals who excel in collaborative environments, communicate effectively, and approach challenges with a problem-solving mindsetnot just those who follow instructions.
Job Responsibility:
Design, develop, and maintain high-performance data pipelines and ETL/ELT workflows for the enterprise data warehouse
Work with cloud-based data warehouse platforms like Snowflake, BigQuery, or Redshift to optimize data storage and retrieval
Write clean, efficient, and maintainable SQL and Python code for data transformation and automation tasks
Implement and manage CI/CD pipelines for data workflows using tools like Git, Jenkins, or GitHub Actions
Leverage orchestration tools (e.g., Apache Airflow, dbt Cloud, Prefect) to schedule and monitor data workflows
Conduct detailed data analysis between current and target systems, and prepare mapping documentation
Collaborate with data analysts, scientists, and business teams to generate actionable insights
Proactively identify and address data quality issues and performance bottlenecks
Contribute to data architecture decisions and establish best practices
Requirements:
4-15 years of experience in Data Engineering or EDW Development
Strong hands-on experience with Snowflake, BigQuery, or Redshift
Expertise in SQL and Python
Working knowledge of CI/CD tools such as Git, Jenkins, and GitHub Actions
Experience with workflow orchestration tools like Airflow and Prefect
Ability to analyze large datasets and present findings in a business context
Excellent communication and teamwork skills
A proactive, solution-oriented mindset with strong ownership and accountability
Nice to have:
Experience in data modeling and architecture
Understanding data governance, security, and compliance best practices
Familiarity with modern data stack tools such as dbt, Fivetran, or Looker
Experience with large-scale enterprise data warehouse implementations