Cloud storage setup
Configuration of cloud-based storage solutions, such as Amazon S3, Google Cloud Storage, or Azure Blob Storage, to store structured and unstructured data securely and durably in the cloud.
Data processing framework
Implementation of data processing frameworks and tools, such as Apache Spark, Hadoop, or Google Cloud Dataflow, to perform data transformations, analytics, and batch or real-time processing on large datasets.
Database management
Deployment and management of cloud-based databases, such as Amazon RDS, Google Cloud SQL, or Azure Cosmos DB, to store and manage structured data efficiently for transactional and analytical workloads.
Scalability and elasticity
Design of the infrastructure to scale seamlessly based on demand, allowing businesses to handle growing data volumes and workload spikes without performance degradation.
Data integration pipelines
Development of data integration pipelines to ingest, cleanse, transform, and load data from various sources into the cloud data infrastructure, ensuring data consistency and reliability.
Security and compliance
Implementation of security measures such as encryption, access controls, and data governance policies to protect sensitive data and ensure compliance with regulatory requirements such as GDPR, HIPAA, or PCI DSS.
