7 data engineering tools for beginners

Data engineering is an often underrated but highly lucrative field that forms the backbone of data analytics and machine learning. While many gravitate toward data analytics or machine learning, it is data engineers who provide the essential infrastructure and data needed for analysis and model training. With an average salary of $150K USD per year and the potential to earn up to $500K USD.

To start working in this field, it is important to learn tools for data orchestration, database management, batch processing, ETL (Extract, Transform, Load), data transformation, data visualization and data streaming. Every tool mentioned in the blog is popular in its category and used by top-tier companies.

1. Prefect

Prefect is a data orchestration tool that allows data engineers to automate and monitor their data pipeline. It provides an intuitive dashboard and a simple Python API, making it easy for anyone to create and run workflows seamlessly. Prefect allows users to efficiently create, schedule, and monitor workflows, making it a great option for beginners. It also allows you to save results, implement workflow, automate workflow, and receive execution status notifications.

2.PostgreSQL

PostgreSQL is a secure, high-performance open source relational database. It focuses on data integrity, security, and performance, making it a great choice for beginners who need a solid database solution.

PostgreSQL is a popular and sometimes the only choice for all data-related tasks. You can use it as a vector database, data warehouse and optimize it for use as a cache.

3. Spark Apache

Apache Spark is an open source unified analytics engine designed for large-scale data processing. Supports in-memory processing, which significantly speeds up data processing tasks. Apache Spark features resilient distributed data sets (RDD), rich APIs for multiple programming languages, data processing across multiple nodes in a cluster, and seamless integration with other tools. It is highly scalable and fast, making it ideal for batch processing in data engineering tasks.

4. Cincotran

Fivetran is a cloud-based automated ETL (Extract, Transform, Load) platform that simplifies data integration. It automates the extraction of data from various sources, its transformation and loading into a data warehouse. Fivetran's ease of use and automation capabilities make it a great tool for beginners who need to set up reliable data channels without extensive manual intervention.

5. dbt (data creation tool)

dbt is an open source command-line tool and framework that enables data engineers to efficiently transform data within their data warehouses using SQL. This SQL-first approach makes dbt particularly accessible to beginners, as it allows users to write modular SQL queries that are executed in the correct order. dbt supports major data warehouses including Redshift, BigQuery, Snowflake, and PostgreSQL, making it a versatile choice for various data environments.

6. Table

Tableau is a powerful business intelligence tool that allows users to visualize data across their organization. It provides an intuitive drag-and-drop interface for creating detailed reports and dashboards, making it accessible to beginners. Tableau's ability to connect to multiple data sources and its powerful visualization tools make it a great choice for effectively analyzing and presenting data for non-technical stakeholders.

7. Apache Kafka

Apache Kafka is an open source distributed streaming platform used to build streaming applications and real-time data pipelines. It is designed to handle high-throughput, low-latency data streams, making it ideal for real-time data processing. Kafka's robust ecosystem and scalability make it a valuable tool for beginners interested in real-time data engineering.

Final thoughts

These seven tools provide a solid foundation for data engineering beginners, offering a combination of real-time data orchestration, transformation, storage, visualization, and processing capabilities. By mastering these tools, beginners can take a step toward becoming professional data engineers and working with higher-paying companies like Netflix and amazon.

Abid Ali Awan (@1abidaliawan) is a certified professional data scientist who loves building machine learning models. Currently, he focuses on content creation and writing technical blogs on data science and machine learning technologies. Abid has a master's degree in technology management and a bachelor's degree in telecommunications engineering. Their vision is to build an artificial intelligence product using a graph neural network for students struggling with mental illness.

1. Best VPN for Engineers: 3 Months Free – Stay safe online with a free trial

2. The best project management tool for technology teams – Drive team efficiency today

4. The best password management tool for tech teams – zero trust and zero knowledge security