Data Engineer Services

4 weeks ago


Snowflake, United States Infy8 Full time

Data Engineering is a broad field involving the design, construction, and maintenance of systems for collecting, storing, and analyzing data at scale. The top services in data engineering often include cloud-based platforms, databases, ETL (extract, transform, load) tools, data warehousing solutions, and big data processing frameworks. Here's a brief overview of some of the top services commonly used by data engineers, categorized by their primary function: Amazon Web Services (AWS):

Offers a wide range of services such as Amazon S3 for storage, Amazon Redshift for data warehousing, and Amazon EMR for big data processing. Google Cloud Platform (GCP):

Known for BigQuery (data warehousing), Cloud Storage, and Dataflow (stream and batch data processing). Microsoft Azure:

Provides Azure Data Lake for storage, Azure Synapse Analytics (formerly SQL Data Warehouse), and Azure Databricks for big data analytics. Databases

Relational Databases:

PostgreSQL, MySQL, and Microsoft SQL Server are widely used for transactional databases. NoSQL Databases:

MongoDB, Cassandra, and DynamoDB (AWS) are popular for unstructured or semi-structured data. ETL Tools

Apache NiFi:

A powerful and reliable system to process and distribute data. Talend:

Offers open-source and commercial products for data integration, data quality, and data management. Informatica:

A leader in cloud data management with a strong focus on ETL, data quality, and data governance. Data Warehousing

Snowflake:

A cloud-based data warehousing service known for its performance, concurrency, and simplicity. Redshift:

AWS's data warehousing solution, optimized for handling large scale datasets. Google BigQuery:

A fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. Apache Spark:

An open-source distributed computing system for big data processing, known for its speed and ease of use. Apache Hadoop:

A framework that allows for the distributed processing of large data sets across clusters of computers. Databricks:

A platform founded by the creators of Apache Spark, offering a unified analytics platform. Data Orchestration

Apache Airflow:

An open-source platform to programmatically author, schedule, and monitor workflows. Prefect:

A modern workflow orchestration platform designed for simplicity and scalability. Luigi:

Developed by Spotify, Luigi helps you build complex pipelines of batch jobs. These services and tools are essential for data engineers to build scalable, reliable, and efficient data infrastructures.

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