Writing from our team. The latest news, insights, and resources.
Referring a friend to something you genuinely believe in is one of the simplest yet most powerful ways to create opportunities. With that in mind, we’re excited to introduce the Data Engineer Academy Referral Program—a way to reward you for sharing the benefits of industry-leading data engineering training with the people you know. We designed...
In today’s digital world, both individuals and businesses require a powerful website. However, finding a trustworthy hosting company is an important step in creating a website. Amazon Web Services (AWS) EC2 provides a strong and scalable infrastructure for hosting websites, making it a great alternative for your hosting requirements. Step-by-step instructions for how to host...
Data engineering is not one fixed career path. The same job title can mean audit-ready reporting in finance, privacy-heavy pipeline work in health, or product analytics and growth systems in SaaS. That matters if you’re choosing your first role, switching industries, or trying to build the right portfolio. The best path depends on the data...
Here’s the short version: cloud data warehouses store cleaned, structured data for fast analytics. Data lakes store large amounts of raw data in many formats, so teams can process it later. That choice affects cost, query speed, governance, and your team’s daily workflow. If you’re building pipelines, modeling data, or planning cloud architecture, you need...
Neither path is better for everyone. The right move depends on how you want to lead, through deep technical ownership or through people, planning, and team results. That choice matters more in 2026 because data teams now span cloud platforms, analytics engineering, AI support, governance, and platform work. You need to know what the job...
Entry-level data engineer interview preparation is usually about the basics, not fancy tools. Most companies test SQL, Python, databases, ETL concepts, simple cloud knowledge, projects, and how clearly you think through problems. That’s good news if you’re new. You don’t need years of full-time work to interview well. You need solid fundamentals, proof that you...
A data engineering portfolio is proof that you can do the work before anyone gives you the job title. If you’re trying to get interviews without experience, a small set of real projects can do what a blank resume can’t. The fastest path is simple. Build a few focused projects that show SQL, Python, ETL,...
If you’ve sent out dozens of applications and heard almost nothing back, your resume may be losing the fight in the first few seconds. The best data engineer resume tips aren’t about fancy wording. They’re about making your experience easy to spot, easy to trust, and hard to skip. Christopher Garzon, founder and CEO of...
Most data engineering jobs ask for the same base skills: SQL, Python, data modeling, ETL or ELT pipelines, cloud basics, and simple system design. Employers care less about long tool lists and more about whether you can move data, clean it, test it, and explain your choices. That means your goal is not to learn...
A lot of data engineers can write SQL. A lot can talk about Python, cloud tools, and pipelines. Far fewer can handle a data modeling interview well under pressure. That gap matters, because this is one of the fastest ways to separate yourself from the pack. If you want to stand out, you need more...
A data engineering bootcamp helped me most by giving me job-ready skills, hands-on projects, interview practice, and a clear job search plan. I picked that route because learning alone felt slow, messy, and hard to measure. Before the bootcamp, I kept bouncing between courses and tool tutorials. After it, I had a stronger title, better...
The switch made sense fast because backend development and data engineering already share a lot of ground. I was still working with code, databases, APIs, jobs that run in production, and systems that break in annoying ways at 2 a.m. What changed was the kind of problem I wanted to solve. I wanted to work...
BigQuery is Google Cloud’s serverless data warehouse, built to store and analyze huge datasets fast. If you want a future-proof data engineering skill, this is one of the smartest places to start because modern teams want cloud analytics, SQL at scale, and data platforms that can support AI work. You don’t need to know every...
The path is simpler than it looks. To become a data engineer in 2026, learn the core data skills first, build a few real projects, choose one cloud stack, and then grow into a specialty. That path still works because companies still need clean, reliable data for analytics, AI, and automation. Below, you’ll see what...
The rise of artificial intelligence is reshaping industries across the globe, and the field of data engineering is no exception. AI is no longer a tool limited to data scientists and machine learning engineers—it has become a driving force in transforming how data engineers design, build, and optimize data pipelines, systems, and workflows. With the...
Python data visualization interview questions test whether you can choose the right chart, explain your reasoning, and turn raw data into clear insights. Most interviews focus on chart selection, library knowledge, plot customization, storytelling, and handling real-world data issues such as missing values or large datasets. This article aims to guide you through the Python...