Given the massive amount of data collected, managed, and consumed these days, data science roles — such as data engineering — are increasingly important. In this article, we’ll provide an overview of the skills and responsibilities related to data engineering along with many resources to help you get started.
The Raw and the Cooked
“Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale,” says CIO. They create data pipelines that convert raw data into usable formats, and they are “responsible for managing, optimizing, overseeing, and monitoring data retrieval, storage, and distribution throughout the organization.”
In preparing data for analytical or operational uses, data engineers “integrate, consolidate, and cleanse data and structure it for use,” says Ben Lutkevich. They also deal with both structured and unstructured data.
“Structured data is information that can be organized into a formatted repository like a database. Unstructured data — such as text, images, audio and video files — doesn't conform to conventional data models. Data engineers must understand different approaches to data architecture and applications to handle both data types,” Lutkevich explains.
Skills and Responsibilities
The primary goal of data engineering is to make data available, accessible, and secure, says CIO. To do this, a data engineer's toolkit includes skills and technologies related to:
- Cloud computing platforms
- Data ingestion
- Data storage
- Extract, transform, and load (ETL)
- Machine learning frameworks
- Processing frameworks
- Retrieval-augmented generation (RAG)
Data engineers also need to be skilled in various programming languages, such as Java, Python, R, and SQL.
Common responsibilities for a data engineer include:
- Acquire appropriate data sets
- Clean, organize, and prepare data from various sources
- Develop, test, and maintain database pipeline architectures
- Automate manual data processes
- Ensure compliance with data governance and security policies
Courses and Certifications
Online courses can help you acquire data engineering skills; here are a few options to consider:
- Data Engineering with AWS — Udacity
- Data Engineering for Data Scientists — Udacity
- Data Engineering Courses — LinkedIn
- IBM: Data Engineering Basics for Everyone — edX
- Python, Bash and SQL Essentials for Data Engineering Specialization — Duke/Coursera
Popular data engineer certifications include:
- Cloudera Certified Professional Data Engineer
- Databricks Certified Data Engineer Professional
- Data Science Council of America (DASCA) Associate Big Data Engineer
- Google Cloud Professional Data Engineer
- IBM Data Engineering Professional Certificate
Other Resources
Learn more about data engineering from the following resources.
- 11 Data Science Careers Shaping Our Future — Northeastern University
- Big Book of Data Engineering: 2nd Edition — Free ebook from Databricks
- Data Engineering Practice Problems — Daniel Beach
