What technologies and tools do you use when working with large volumes of data?

When working with large volumes of data, the following technologies and tools are often used:

• Hadoop — a distributed file system and ecosystem for processing big data.
• Apache Spark — a fast in-memory data processing engine suitable for analytics and ETL.
• Kafka — a messaging system for streaming data.
• Elasticsearch — a search engine well-suited for indexing and quick searches over large data volumes.
• NoSQL databases (e.g., MongoDB, Cassandra) — for storing unstructured or semi-structured data.
• SQL databases with scalability support (e.g., Greenplum, Amazon Redshift) — for analytical queries.
• Orchestration and automation tools (Airflow, Luigi) — for managing data processing workflows.

Also important are skills in working with cloud platforms (AWS, GCP, Azure), which provide scalable services for storing and processing big data.