DESCRIPTION OF THE TASKS
Development and maintenance of a fully open-source Data Lakehouse.
Design and development of data pipelines for scalable and reliable data workflows to transform extensive quantities of both structured and unstructured data.
Data integration from various sources, including databases, APIs, data streaming services and cloud data platforms.
Optimization of queries and workflows for increased performance and enhanced efficiency.
Writing modular, testable and production-grade code.
Ensuring data quality through monitoring, validation and data quality checks, maintaining accuracy and consistency across the data platform.
Elaboration of test programs.
Document processes comprehensively to ensure seamless data pipeline management and troubleshooting.
Assistance with deployment and configuration of the system.
Participation in meetings with other project teams.
KNOWLEDGE AND SKILLS
Extensive hands-on experience as Data Engineer or Data Architect in modern cloud-based open-source data platform solutions and on data analytics tools.
Excellent knowledge of data warehouse and/or data lake house design & architecture.
Excellent knowledge of open-source, code-based data transformation tools such as dbt, Spark and Trino.
Excellent knowledge of SQL.
Good knowledge of Python.
Good knowledge of open-source orchestration tools such as Airflow, Dagster or Luigi.
Experience with AI-powered assistants like Amazon Q that can streamline data engineering processes.
Good knowledge of relational database systems.
Good knowledge of event streaming platforms and message brokers like Kafka and RabbitMQ.
Extensive experience in creating end-to-end data pipelines and the ELT framework.
Understanding of the principles behind storage protocols like Apache Iceberg or Delta Lake.
Proficiency with Kubernetes and Docker/Podman.
Good knowledge of data modelling tools.
Good knowledge of online analytical data processing (OLAP) and data mining tools.
Ability to participate in multilingual meetings
Ability to work with a high degree of rigour and method and, more specifically, to follow naming conventions and coding standards.
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