7 Essential Resources to Start Your Journey in Data Engineering

The world is generating more data than at any point in history. As digital services multiply and businesses depend more heavily on analytics, the demand for professionals who can design reliable, scalable data systems has skyrocketed. Data engineering—once a niche skill—has become one of the fastest-growing roles in the data ecosystem.

Statista projects that global data volume will expand from 26 zettabytes in 2017 to roughly 175 zettabytes by 2025, a staggering 573% increase. This growth follows an earlier explosion of nearly 800% between 2010 and 2016. With this surge comes a pressing need for engineers who understand how to collect, store, transform, and optimize data at scale.

If you’re looking to break into the field or strengthen your skills, here are seven learning paths and certifications worth exploring.

1. Microsoft Certified: Azure Data Engineer Associate

Level: Advanced

This certification focuses on building and managing end-to-end data solutions using Azure’s extensive suite of tools. Candidates learn how to design secure, monitored, and efficient architectures across Azure storage, analytics, and data processing services. The curriculum is structured as a set of short learning modules—most under ten hours—followed by the official exam.

2. Udacity Data Engineering Nanodegree

Level: Beginner (some prerequisites recommended)

Udacity’s Data Engineering Nanodegree provides hands-on training in the technologies used to build modern data pipelines. Over approximately five months, learners work with SQL, Apache Spark, Airflow, and AWS-based data warehousing solutions. It is built to bridge the gap between entry-level skills and real-world engineering demands.

3. Google Cloud Platform: Professional Data Engineer

Level: Advanced

Google’s professional-level certification is aimed at individuals already comfortable with cloud technologies. Google recommends pairing the exam with Qwiklabs’ Data Engineering on Google Cloud Platform course for guided practice. The training covers Hadoop ecosystems, BigQuery, real-time processing tools, and how to deploy scalable machine learning workflows.

4. Dataquest: Data Engineer Career Path

Level: Beginner

This interactive career track is an excellent starting point for newcomers. The program begins with Python fundamentals and progresses into SQL, PostgreSQL, data structures, and algorithmic thinking. While the content is beginner friendly, a basic familiarity with Python is helpful. The curriculum focuses on practical skills for real-world data engineering.

5. UC San Diego Big Data Specialization (Coursera)

Level: Beginner

Developed in collaboration with Splunk, this Coursera specialization introduces learners to the foundations of big data through Hadoop and Apache Spark. The series builds up to applying big-data techniques in a machine-learning scenario. No prior programming experience is required, though the course does have specific software and hardware prerequisites.

6. AWS Certified Big Data / Data Analytics – Specialty

Level: Advanced

As the largest cloud provider, AWS remains a key player in the data engineering landscape. Its specialty certification validates deep expertise across AWS analytics tools, including Redshift, Kinesis, EMR, Glue, and more. The updated version of the exam—renamed AWS Certified Data Analytics – Specialty—is designed for engineers with several years of hands-on AWS experience and foundational cloud certifications.

7. The Data Engineering Cookbook – Andreas Kretz

Level: Intermediate to Advanced

This comprehensive guide by Andreas Kretz offers practical insights drawn from real-world data engineering workflows. Known for his “Plumbers of Data Science” podcast, Kretz breaks down complex topics into an approachable learning path. The book is freely available and frequently updated, making it a valuable resource for aspiring and experienced engineers alike.

Final Thoughts

With data volumes growing at unprecedented rates, organizations depend on data engineers to build systems that are efficient, scalable, and reliable. Whether you’re just beginning your journey or looking to advance your expertise, these seven resources provide structured pathways to building strong, industry-ready skills.

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