Descrizione
Accountabilities
- Design, develop, maintain, and optimize data pipelines using Azure Databricks, PySpark, Azure Data Factory (ADF), Python, and Azure Data Lake.
- Build and support ETL/ELT processes to integrate enterprise data and meet analytical and business requirements.
- Perform data ingestion, transformation, validation, and reconciliation across multiple source systems.
- Conduct data profiling and quality assessments to identify inconsistencies, resolve issues, and ensure data accuracy and reliability.
- Develop, write, and optimize complex SQL queries to improve data processing performance.
- Perform performance tuning and troubleshoot large-scale data workloads to ensure efficiency, scalability, and reliability.
- Provide Level 2 production support for incidents involving Azure Data Factory pipelines, Databricks jobs, and data processing workflows.
- Monitor and maintain production pipelines, ensuring availability, operational stability, and efficient resource utilization.
- Support deployment and release processes across development, testing, and production environments.
- Manage competing priorities across multiple projects, working independently while meeting deadlines and maintaining high delivery standards.
- Requirements More than eight years of professional experience in data engineering, including the development and maintenance of ETL processes.
- Strong hands-on experience with Azure Databricks and Azure Data Factory (ADF).
- Extensive knowledge of ETL/EL
Descrizione completa, azienda e link per candidarti: dopo l'accesso.
AccediI contatti del datore di lavoro (email/telefono/telegram) sono nascosti nell'anteprima pubblica.
Invia il tuo CV così i datori di lavoro possono contattarti direttamente.