
Cloud Solutions Architect
20 hours ago
The role of a Cloud Data Engineer involves designing and implementing scalable data pipelines, building and maintaining robust data lakes, and working with various data platforms.
- Design and Development:
- Develop and maintain scalable ETL pipelines using cloud-native tools such as AWS DMS, AWS Glue, Kafka, Azure Data Factory, GCP Dataflow, etc.
- Architect and implement data lakes and data warehouses on cloud platforms like AWS, Azure, and GCP.
- Develop and optimize data ingestion, transformation, and loading processes using Databricks, Snowflake, Redshift, BigQuery, and Azure Synapse.
- Implement ETL processes using tools like Informatica, SAP Data Intelligence, and others.
- Develop and optimize data processing jobs using Spark Scala.
- Data Integration and Management:
- Integrate various data sources, including relational databases, APIs, unstructured data, and ERP systems into the data lake.
- Ensure data quality and integrity through rigorous testing and validation.
- Perform data extraction from SAP or ERP systems when necessary.
- Performance Optimization:
- Monitor and optimize the performance of data pipelines and ETL processes.
- Implement best practices for data management, including data governance, security, and compliance.
- Collaboration and Communication:
- Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
- Collaborate with cross-functional teams to design and implement data solutions that meet business needs.
- Documentation and Maintenance:
- Document technical solutions, processes, and workflows.
- Maintain and troubleshoot existing ETL pipelines and data integrations.
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