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• Minimum of 5 years of professional experience in Data Engineering.
• Proven experience designing and implementing data architectures and ETL processes.
• Proficiency in data engineering tools and languages (e.g., Python, SQL, Apache Spark).
• Experience with data warehouse platforms (e.g., Amazon Redshift, Google BigQuery, Snowflake).
• Familiarity with cloud platforms (AWS, GCP, or Azure).
• Strong understanding of data modeling concepts and the ability to design effective data models.
• Data Governance: Knowledge of data governance principles, data quality management, and data security best practices.

• SQL
• Python / Java
• ETL

• Design, implement, and maintain scalable and efficient data architectures, including data warehouses, data lakes, and ETL processes.
• Lead the development of robust and scalable Extract, Transform, Load (ETL) processes to ensure the seamless flow of data between systems.
• Collaborate with cross-functional teams to integrate data from various sources, ensuring data quality, consistency, and accuracy.
• Develop and implement data models to support business requirements, ensuring data is structured for optimal performance and analytical capabilities.
• Identify and address performance bottlenecks within the data infrastructure, optimising queries and processes for efficiency.
• Implement and enforce data governance policies, ensuring compliance with data privacy regulations and maintaining data security.
• Implement automation strategies for data processing, monitoring, and maintenance tasks, reducing manual intervention and improving reliability.

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  Discover exclusive long-term remote engagements at the world’s most interesting product companies.
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• A recruitment process that values your time
  Only one hiring process with the possibility of several positions, without any additional tests.