All Gambill Data Blogs
SQL's Hidden Travel Itinerary: One Join Could Derail Everything
A single INNER JOIN nearly derailed a $7M pipeline. Learn how misunderstanding SQL’s execution order, JOIN logic, and window functions can quietly break dashboards—and how to fix it. Includes a practical breakdown and real-world debug challenge.
AI Is the Atomic Age of Our Time
We are living in a transformational moment. A moment that rivals the birth of nuclear energy. AI isn’t just another tech trend. It’s a force-multiplier for decisions, predictions, and influence. And like the Atomic Age before it, AI brings with it the question that matters most:
Will we build it responsibly? Or let it become something we can’t control?
Don’t Bolt On Your Data Team Build Them In From the Start!
Not long ago, I was leading a data team at a company going through a major transformation: integrating a new marketing platform and changing field structures in Salesforce. But here’s the thing—we weren’t part of the project team.
In fact, we only got involved three weeks before go-live.
And not because we were officially brought in…
But because I overheard the conversation during a cross-functional meeting.
Let me walk you through what happened and why it’s a warning signal for any business undergoing change.
5 Common Pitfalls Every New Data Engineer Faces
Starting your journey as a data engineer can feel exciting and overwhelming at the same time. You're learning new skills, building your first pipelines, and discovering just how messy real-world data can be. But don’t worry—you're not alone! I've been there, and today I'll walk you through five common pitfalls that new data engineers often face, along with practical advice on how to avoid them.
You Are NOT Ready for a Senior Data Engineer Role!
So, you’ve been writing SQL, building pipelines, maybe even mentoring a junior teammate here and there…
You’ve got experience. You’re good at what you do. But here’s the hard truth:
You are NOT ready for a senior data engineer role—unless you’ve done the hard part.
And the hard part?
It’s not mastering another tool. It’s not adding one more cloud cert.
It’s about proving that you can think, lead, and deliver like a senior.
Let me explain…
Gambill’s Gauntlet: Master Data Engineering Interviews One Question at a Time
I’ve created Gambill’s Gauntlet … born from my 25+ years of experiencing both sides of the interview table. This isn’t just another tutorial series. It’s an interactive weekly challenge designed to transform interview anxiety into interview mastery.
Each week, you’ll face authentic interview questions that have stumped even seasoned engineers
Your Data Governance Is Failing!
Have you noticed more and more "creative" solutions popping up across your business units? Are teams independently generating data products and reports that seem to bypass your centralized data governance processes?
If so, you're experiencing a common symptom of failing data governance—and it’s a bigger problem than you might realize.
Data Engineering: Fueling Better Business Decisions
Imagine trying to navigate a complex city without a map or GPS. You might eventually reach your destination, but you'll likely waste valuable time and resources in the process. Similarly, businesses operating without strong data engineering practices often find themselves navigating critical decisions blindly, relying heavily on intuition or incomplete information.
Automating EDA & Handling Schema Drift: From Excel to Python
If you've ever imported a dataset only to find that column names have changed, critical fields are missing, or dates are stored in different formats, you've experienced schema drift. Manually inspecting these differences in Excel is fine for a few files, but what if you have hundreds of datasets spanning multiple years?
Automating Data Pipelines with Python Classes and Functions
Handling new CSV files manually can be time-consuming and prone to errors. If you've ever had to inspect a CSV file, determine its schema, create a table, and then load the data manually, you know how tedious it can be. In this post, I’ll walk you through a Python class that automates this entire process—from reading a CSV file to dynamically creating a staging table and loading the data into a database.
This solution is great for data engineers and analysts who need a flexible, reusable approach to handling structured data.
6 Data Skills That Will Get You Hired in 2025!
The world of data engineering is evolving at a exponential pace. Companies are handling more data than ever, and they need talented data professionals who can optimize performance, automate processes, and communicate insights effectively. If you want to land a high-paying job in data engineering in 2025, these are the six transformational skills that will set you apart from the competition.
5 Must-Know Tools for Data Engineers in 2025
The data engineering landscape is evolving fast, and if you want to stay ahead in 2025, you need to master the right tools. Some of these have been industry staples for years, while others are gaining traction as must-know technologies. And at the end, I’ll introduce you to a brand-new tool that could change the face of data engineering!
Prioritizing DEI in Tech: The Importance of Diversity
Tech is built by all of us, for all of us—but are we doing enough to ensure everyone’s voices are included?
Diversity isn’t just about fairness—it’s about innovation, better decision-making, and stronger teams. Studies show that diverse teams solve problems faster and build better products, yet women and underrepresented groups still face barriers in tech.
Deepseek and Mage AI: Transforming Data Engineering
Artificial Intelligence is a vast field with many moving parts—and not all AI is created equal. In today’s data-driven world, two paradigms are often talked about: generative AI and predictive AI. Although these terms might seem interchangeable to some, they serve very different purposes. In this article, we’ll explore the key differences between generative and predictive AI, discuss their unique roles in data engineering, and highlight innovative tools like Deepseek and Mage AI that are helping businesses modernize their operations.
The DP-203 Retirement and the Rise of DP-700 Fabric Data Engineer Exam
Big news for data engineers! Microsoft is retiring the DP-203 exam at the end of March 2025, and in its place, they’re introducing the DP-700 Fabric Data Engineer certification. If you're working in the Azure ecosystem, this shift marks a significant change in the way Microsoft envisions the future of data engineering. In this blog, we'll break down what’s happening, why Microsoft is making this change, and whether DP-700 is worth pursuing.
Quality Over Hype: When Is the Right Time to Invest in a Data Solution?
Before adopting AI, cloud platforms, or advanced analytics tools, businesses must focus on data quality, structure, and governance. Investing in the latest technology without addressing these fundamentals can lead to costly mistakes, wasted resources, and inaccurate insights. In this blog, we explore when is the right time to invest in a data solution and how to build a strong data foundation that drives real value.
How to Ace Your Data Engineering Interview: Top Questions and Winning Answers
Preparing for a data engineering interview? This guide breaks down the most common technical, soft skills, and problem-solving questions you’ll face—and provides winning answers to help you stand out. Learn how to:
Write efficient SQL queries and optimize performance.
Answer soft skills questions using the STAR method.
Design scalable data pipelines for real-time processing.
Craft a standout answer to ‘What makes you unique?’
Whether you’re an aspiring data engineer or a seasoned professional, these tips will help you walk into your interview with confidence and walk out with the job offer. Save this article for your next interview prep!