How Can Data Engineers Leverage AWS Services for Scalable Data Pipelines?
Data engineers can effectively leverage AWS (Amazon Web Services) to build scalable, secure, and cost-effective data pipelines by using a suite of fully managed services tailored for each step in the data lifecycle — from ingestion and processing to storage and analysis. Here’s how data engineers can use AWS services at each stage of the pipeline: ✅ 1. Data Ingestion AWS provides services that allow the ingestion of batch, streaming, and real-time data. Services: Amazon Kinesis (Data Streams, Firehose): Ingest streaming data from sources like IoT devices, logs, clickstreams. Firehose can directly deliver data to S3, Redshift, or Elasticsearch. AWS Glue DataBrew : For visual data preparation and profiling. AWS Snowball / Snowmobile : For large-scale, offline data transfers. Amazon S3 : Simple, durable storage used to land batch files, logs, and other datasets. ✅ 2. Data Processing & Transformation Transform raw data into usable fo...