In this 2025 YouTube video, former pizza delivery worker turned self‑taught data scientist Kedisha Bryan argues that high‑paying remote tech jobs do not require a college degree or extensive coding experience. She outlines three specific roles—Data Analyst, Data Engineer, and Analytics Engineer—detailing day‑to‑day responsibilities, the minimal tech stack needed for each, typical salary ranges ($80K‑$150K), expected time to become job‑ready (3‑9 months), and an ROI score she assigns to each role. Kedisha emphasizes transferable skills from non‑tech backgrounds, the importance of building a personal brand and a portfolio of real projects, and warns about common pitfalls such as low‑quality resumes and hidden job titles. Throughout, she uses motivational coaching language, shares success anecdotes of career changers she has coached, and concludes with a call‑to‑action to book a free one‑on‑one roadmap call for personalized guidance.
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Most people still think you need a degree or experience to land a 6-figure remote job, but they're dead wrong. I used to work at a warehouse and deliver pizzas for just $8 an hour, and now I work from home and make over 6 figures. No extra degree, just a smarter path that nobody else was talking about. And here's the kicker. Some of the highest paying remote roles don't even require experience or even a bunch of lines of code. Or a single college class. And yet they're hiring like crazy. Why? Because barely anyone knows these jobs exist. That's why the competition is so low and the pay is so high. And I've helped everyone from teachers to truck drivers land roles like these in as little as 90 days. These are real jobs, real paychecks, and real results. So before someone else snags the role that should have been yours, watch this video until the end. Because I am breaking down 150K remote jobs that you've never heard of and how to get one starting from scratch. If this is your first time here, my name is Kedisha and I used to deliver pizzas and now I deliver insights as a self-taught data scientist. And I've coached thousands of other career changers how to break into data without going back to school. And I'm here to teach you how to do the same. So let's dive in. So first up, data analyst. Let's be honest, this title sounds very basic and most people will scroll right past it, but that's exactly why This one is one of the biggest missed opportunities in tech right now. Because here's the truth. There are over 300,000 open data analyst roles on LinkedIn right now. Many of them pay $80,000 to $120,000 fully remote. And most people still think they need a degree or an expensive $20,000 bootcamp to qualify. You don't. In fact, this is one of the easiest remote roles for career changers to pivot into. Fast, and this is why. You already have the transferable experience, whether it's tracking KPIs, reporting numbers, or just making decisions based on any type of results. The tech stack is also very simple compared to other remote roles in tech, and the barrier to entry is pretty low, but the ceiling is very high. So what exactly do you do as a data analyst? You solve problems with data. You dig through the numbers to answer critical questions like, why are sales down this quarter? Which product is causing the most complaints? And where are we losing money? You are not just creating charts or crunching numbers. You are turning noise into insights and insights into action. And guess what? You can do all of this from your couch. Here's the tech stack that you'll need. Excel, master pivot tables, lookups, and basic stats. SQL, pull clean and join data like a pro in databases. Tableau or Power BI, build dashboards that tell a clear visual story. PowerPoint, present findings like a consultant. Not a college student. Python, totally optional, but adds firepower once you're ready to level up. But let's keep it real. What are the downsides? Yeah, there's demand, but there's also a lot of noise. Tons of people are applying to these jobs, but honestly, most of them aren't ready. They're submitting half-baked resumes, copying tutorials, and hoping for the best. And that's where you win. If you build a brand. When you show proof, real projects, real insights, real value, you rise above the noise. I've coached many people from all types of backgrounds into these roles, trucking, admin, education, no extra degree required. I'm giving a data analyst the ROI score of 9.2 out of 10. Over 300K roles hiring right now, remote friendly, flexible and scalable, accessible skill stack with real upward mobility, career changer friendly with fast pivot potential. The downsides. Lots of applicants to these roles, but many lack substance. If you don't build a brand and showcase proof, you'll get buried in the pile. But that won't be you. You're learning the game the right way. Now, if you're someone who wants to work behind the scenes, automate the hard stuff, and get paid like an architect of the internet, let's talk about the data engineer. Now, this one is not for everyone, but the payoff is huge. If a data analyst is the detective, the data engineer is the architect. You're not just looking at the data, you're building the entire pipeline that delivers And while this role doesn't get all the social media hype, let me tell you something. Data engineers are making over $100,000 straight out the gate and can scale to $150K in just under 2 years. This is one of the most financially rewarding remote roles in tech, period. But unlike the data analyst, this isn't an easy pivot. Let's keep it real. It takes more time to learn. There are fewer true entry-level roles, and you need to be comfortable getting deep into technical systems. So what exactly does a data engineer do? You build systems that collect, clean, move, and store massive amounts of data. Think of it like being the data plumber. You make sure the right info flows to the right people on time and without errors. You're not building dashboards, you're building what makes dashboards possible. And while this might sound niche, every company needs this because when their data is broken, Nothing works. Not the reporting, not the insights, not the strategy. That's why data engineers are some of the most highly valued people in the room. Now, what skills do you need? Let's break it down. SQL, deep level querying, joins, optimization. This is foundational. Python for automation, transformation, and building data pipelines. Command line, you'll deploy code, manage files, and troubleshoot from the terminal. ETL tools like Airflow or dbt to schedule and orchestrate data flows. Cloud platforms like AWS, GCP, or Azure, pick one, learn the core services, data warehousing, Snowflake, Redshift, BigQuery, pick one and understand the architecture. So what's the deal from here? If you want quick wins, this isn't your lane. This is a long game and that's what makes it worth it. It might take you 6 to 9 months or even more to truly be job ready. You will need deep portfolio projects, not just pretty visuals, and the entry-level market's smaller than you think. You're more likely to land your first role with a hybrid title, like a data analyst/engineer, or through a contract-to-hire situation. But if you love building systems, automating chaos, and solving tough backend problems, you'll thrive here. Don't expect handholding or shortcuts though. This is a high value role, but you need to show receipts that you know what you're talking about. I'm giving the data engineer an ROI score of 8.2 out of 10. Extreme high salary ceiling, high impact, high leverage work. Long-term job security with exploding demand. Still accessible to career changers with patience and proof. But the downsides, it takes longer to learn. So expect 9+ months to be job ready. And there's fewer entry-level or career changer friendly roles. This is the role that pays you like an architect because you're literally building the data infrastructure companies rely on every day. But maybe you want something that sits between an analyst and an engineer, a role that blends business logic with engineering systems with exploding demand. That's exactly what the analytics engineer is. This is the role most people don't even know exists, but it's the sweet spot between an analyst and an engineer. Think of it like this. You're not just answering business questions like an analyst, and you're not just buried in infrastructure like a data engineer. You're building the tools that let analysts do their job faster and smarter. You create clean, organized data models. Use standardized logic, and you make sure everyone in the company is working from the same source of truth. In other words, you are the translator between business goals and engineering systems, and companies are desperate for people who can do this well. So what exactly does an analytics engineer do? Your day-to-day might look like transforming raw data into usable datasets using dbt or SQL, building logic so data analysts don't duplicate, creating and automating dashboards and reports for decision makers, and creating documentation standards and reusable code for future analysts. You add structure, clarity, and scale. This is the tech stack you'll need. SQL, dbt, cloud platforms, Power BI or Tableau, data warehousing, basic understanding of business metrics and stakeholder needs, and command line or Git. It's more technical than a data analyst, but not as hardcore as a data engineer. And that's what makes it so powerful. It's very attainable for career changers who's already picked up SQL and dashboarding skills. You'll need to learn how to think like an engineer, but you don't have to build an entire infrastructure from scratch. And companies love hiring analytics engineers because they fill the gap between teams. They help avoid costly mistakes and wasted time from disconnected data. Here's a truth though. Many job postings don't necessarily say analytics engineer. You'll often find these roles under titles like BI developer, even senior data analyst. That's why you need to learn how to read between the lines and brand yourself correctly. I've seen career changers level up from analyst roles into analytics engineer in under a year just by learning dbt, structuring their SQL projects better, and leveling up their dashboarding and data storytelling skills. I give the analytics engineer a 9.3 out of 10. Why? High pay, hybrid skillset, exploding demand in modern data stacks, career changer friendly if you've already mastered tools like SQL, dashboarding. Downsides, it takes more time to learn. Also often hidden behind misleading job titles. Bottom line, if you like logic, structure, and bridging the gap between people and code, this is your role. And it's one of the smartest long-term moves you can make if you're coming from a non-traditional background. So if you're serious about landing one of these 6-figure remote jobs, go ahead and book a free roadmap call with me down in the description and the pinned comment below. This is going to be a one-on-one session where we figure out where you are now, where you want to be, and Help you build a custom plan to get there. We'll also see if you're a good fit to work with us or not. This is how you come out of the learning curve, stop wasting time, and get real results faster. And that's exactly what we've done to help other career changers who were stuck, overlooked, and just starting from scratch. And now they're getting offers, interviews, and working in the field. And if you want to see the full strategy behind what they did, you can click the video right here.
