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...
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...
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...
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...
Most data modeling interview questions test the same core skill: can you design tables, choose keys, handle changing data, balance clean structure with speed, and explain your tradeoffs clearly? That’s what hiring teams want to know, because good models shape analytics, reporting, data quality, and even pipeline behavior. In real work, a weak model causes...
If you’ve ever wanted your SQL query to return a custom label like “Low,” “Medium,” or “High,” a SQL CASE statement is the tool that gets you there. It adds conditional logic to your output, not by filtering rows like WHERE, but by creating a brand-new column based on rules you define. That’s what makes...
Microsoft data engineer interviews usually test SQL, ETL design, Azure data services, data modeling, system design, and communication. This guide gives you 20 likely interview questions grouped by topic, plus practical advice on how to prepare for technical and behavioral rounds. It is most useful for candidates preparing for Microsoft-focused data engineering interviews or similar...