Ready to become a data engineer? Follow our structured Data Engineer Career Track to master the essential skills to build and maintain data pipelines—from foundational programming to advanced data architecture.
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of professionals must earn to maintain their licenses and stay current with regulations and best practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's official website: www.nasbaregistry.org
Accreditedcertificate
Your data engineer career begins
Data engineers design, build, and maintain the systems that move and organize data at scale. It’s one of the fastest-growing jobs in tech.
Our data engineering courses teach you real-world skills. You follow a data engineer roadmap, complete real AI and data projects that simulate the job, and earn an accredited certification.
We’ve paved your path into a future-proof field—without going back to school. So that you can land a high-paying job. Our data engineer training helps you get there with experts who’ve done it themselves.
Curriculum
Certificates
Student outcomes
Careers
More career paths
Overview
Becoming a data engineer takes more than just watching tutorials. It takes the right guidance, a clear structure, and the chance to practice what the job actually looks like.
That’s why we created this data engineer career path—a step-by-step program that helps you go from complete beginner to a certified data engineer.
As you move through our data engineering training, you’ll follow a curated roadmap:
SQL and Python
Data ingestion and cleaning
Cloud computing fundamentals
Pipeline orchestration with Apache Airflow
Data warehousing and architecture
This data engineering program is built around real tools and job-focused skills. You’ll use what professionals actually use in their daily work.
Instead of stopping at theory, you’ll design end-to-end data pipelines, practice building cloud-based solutions on AWS and GCP, and master the tools that top employers request in thousands of job postings.
Each course in the roadmap builds toward practical milestones, so by the time you complete the data engineer training, you’ll not only understand how data systems work—you’ll have built them.
But learning is just one part. You’ll also work toward a data engineer certification that proves you’ve trained, practiced, and delivered.
Curriculum
CPE credits
ONLINE COURSE
Intro to Data Engineering
Begin your data engineer career path with an introduction to the role, the tools, and the impact of data engineering. Understand how this fast-growing field powers modern data infrastructure.
Master SQL—the language of data. Learn how to query and manage relational databases confidently, a foundational skill in every data engineering course.
Build your programming foundation with Python. Essential for automating data workflows and a core part of every successful data engineer roadmap that prepares you for both scripting and advanced analytics tasks.
Our data engineer training taches you to ingest data from APIs, JSON, databases, and flat files using pandas. Develop practical skills for building data pipelines that real data engineers rely on.
Any data engineer career path requires cloud platforms like AWS, Azure, and GCP. Get a strong foundation in cloud services—critical knowledge for earning a big data certification.
In our data engineer training, you design scalable systems and learn how data engineering enables modern businesses. Understand how to structure and optimize data at scale.
Automate workflows and build production-grade pipelines. Gain experience with Airflow and orchestration tools used in professional data engineer training so you can manage complex, multi-step data processes at scale
Begin your data engineer career path with an introduction to the role, the tools, and the impact of data engineering. Understand how this fast-growing field powers modern data infrastructure.
Master SQL—the language of data. Learn how to query and manage relational databases confidently, a foundational skill in every data engineering course.
Build your programming foundation with Python. Essential for automating data workflows and a core part of every successful data engineer roadmap that prepares you for both scripting and advanced analytics tasks.
Our data engineer training taches you to ingest data from APIs, JSON, databases, and flat files using pandas. Develop practical skills for building data pipelines that real data engineers rely on.
Any data engineer career path requires cloud platforms like AWS, Azure, and GCP. Get a strong foundation in cloud services—critical knowledge for earning a big data certification.
In our data engineer training, you design scalable systems and learn how data engineering enables modern businesses. Understand how to structure and optimize data at scale.
Automate workflows and build production-grade pipelines. Gain experience with Airflow and orchestration tools used in professional data engineer training so you can manage complex, multi-step data processes at scale
When you complete the career track and pass the final exam, you earn an accredited data engineer certificate—recognized globally as proof of your expertise in SQL, Python, data pipelines, and cloud infrastructure.
Accredited by the Association of Data Scientists (ADaSci)
Accredited as an eLearning Quality Network provider (ELQN)
Quality accreditation granted from the European Agency for Higher Education & Accreditation (EAHEA)
Approved CPE* provider under NASBA—our AI bootcamp qualifies for continuing education credit
Reviewed by the Institute of Analytics (IoA)
Member of the Global Association of Online Trainers and Examiners (GAOTE)
*Note: CPE credits are reflected per course in your official transcript, in line with accreditation requirements
"My journey in data started during the pandemic, when I joined 365 Data Science. The well-organized roadmap took me from basic topics like SQL to advanced concepts, helping me transition from a beginner to a professional data engineer. I built strong foundations in Python and SQL, which launched my career in data analysis and engineering. Even now, 365 continues to boost my skills and career growth, thanks to its engaging and well-structured courses."
Nada A.
Before 365:
Business Intelligence Developer at Telecom
After 365:
Senior Data Engineer at VOIS
"One of the biggest takeaways from the bootcamp was the ability to tackle real-world data problems. During my job interview, I was given a practical task by the hiring managers, and thanks to the skills I gained from 365 Data Science, I was the only candidate who solved it! After this, I was hired as a BI developer and have now moved up to a data engineer."
Kristiyan Y.
Before 365:
Payments Agent at 1ForFit
After 365:
Data Engineer at DSK Bank
"With years of experience in Big Data, NoSQL, and data analytics, I turned to 365 Data Science to refresh my knowledge and learn evolving techniques. The professional, well-structured courses helped me review key concepts and discover new approaches that simplify my work and open new job opportunities. Even as an experienced professional, I've found 365 invaluable for staying up to date—and I'm now preparing for the AI Engineer certification."
Mauro L.
Before 365:
Data Analyst and Administrator
After 365:
Big Data Engineer and Data Scientist at Worldline Italia
"365 Data Science taught me how to understand, interpret, and visualize data—skills I've applied to reduce program costs, improve data quality, and streamline reporting in my NGO role. Using techniques like confidence intervals, I optimized commodity redistribution, cutting frequency and saving resources. I've advanced from Excel to SQL and Python, tackling real-life problems as a data engineering intern. 365's structured courses have made my career transition smoother and boosted my impact in both roles."
Victor A.
Before 365:
Medical Laboratory Scientist pivoting to data-focused work in a Health NGO
After 365:
Data Engineer Intern at APIN Public Health Initiatives
Most data engineer career paths begin with a degree in computer science, engineering, information systems, or mathematics. Our 2025 research shows that engineering degrees appear in 77% of job postings, followed by computer science, and data engineering.
However, a degree isn’t always required—26% of postings don’t mention an education level. This reflects a growing shift toward skills-based hiring.
А data engineer certificate and portfolio can carry more weight than a diploma.
If you’re coming from a non-technical field, you can still change careers. Our Data Engineer Career Track provides structured theory, hands-on projects, and accredited data engineer certification—so you gain the exact competencies employers expect. Enroll to take the first step today.
Step 2
Skills
Our analysis of 1,000 data engineer jobs shows that Python, SQL, and Java are core requirements. And in-demand tools include Apache Spar and Snowflake. Cloud proficiency is also critical, with AWS and Azure leading the rankings. Employers also value data modeling, ETL, and orchestration with Apache Airflow. A certified data engineer is expected to have basic data visualization capabilities with tools like Tableau and Power BI.
All these data engineer skills are learnable online. Fast.
Portfolios matter more than resumes. Don’t just list skills—demonstrate them through real projects. In our data engineering courses, you design pipelines and work with large-scale data systems. Today, companies care less about where you learned and more about what you can do. That’s why AI and data science projects are at the heart of our data engineer career path. Explore our data engineer training now.
Step 3
Branding
Your personal brand can open doors to data engineer jobs before you even send an application. Verified data engineer certification from respected providers instantly boosts your credibility. A tailored resume and cover letter—optimized for data engineering roles—show recruiters you understand the job. GitHub repositories tell hiring managers you can design data pipelines, model databases, and work with big data tools.
We noticed that skills-first hiring keep raising, so—tidy up your portfolio.
Profiles featuring accredited data engineer certificates (like those earned through our Data Engineer Career Track) often rank higher in recruiter searches on LinkedIn. With our CPE-accredited data engineering courses—which we’ve included in the data engineer roadmap—you add a layer of trust that hiring managers need. Join our certified data engineering training.
Step 4
Job Search
The data engineer job market in 2025 remains strong but competition is fierce—especially since most roles require 2–6 years of experience and only a small fraction are truly entry-level. Employers want proof that you can design pipelines, work with big data tools, and deploy solutions before they schedule an interview. Good data engineer training like ours lets you practice with mock interviews.
Tap into our insider job newsletter to spot opportunities before they hit public boards. Follow emerging data engineer hiring trends so you know what recruiters are looking for. Most importantly, don’t job-hunt alone. Our mentors and student community help you stay motivated and accountable until your first offer letter lands. Follow your dream of becoming a data engineer career.
You like building strong foundations—designing systems that help data flow smoothly and reliably. That’s the heart of data engineering.
Our free career quiz reveals whether you should learn data engineering or explore another role in AI and data science that better suits your strengths—in just 5 minutes.
A certified data engineer designs, builds, and maintains the systems that collect, store, and process large volumes of data. They work with databases, big data tools, and cloud platforms to create pipelines that ensure data is accessible, reliable, and ready for analysis. While analysts interpret data and data scientists build predictive models, data engineers provide the infrastructure that makes this work possible. If you want to learn data engineering from scratch, the 365 Data Science Data Engineer Career Track covers every step?from SQL and Python to ETL, cloud computing, and data pipeline orchestration?so you graduate job-ready.
What are the best career paths for data engineers?
Entry-level data engineer jobs have several high-growth paths. Common options include: Senior data engineer ? leads complex pipeline projects and mentors junior engineers. Data architect ? designs enterprise-scale data systems. Machine learning engineer ? builds ML-powered data solutions. Analytics engineer ? bridges data engineering with business intelligence. Following a structured data engineer roadmap helps you specialize while expanding into related roles. The 365 Data Science program prepares you for these paths through hands-on training with big data tools, cloud platforms, and real-world projects.
What is the typical data engineer career path: skills, salary, and growth opportunities?
The typical data engineer career path starts with core skills?Python, SQL, ETL processes, and cloud platforms like AWS. Junior roles may begin around $120K, with experienced engineers earning $160K, and senior specialists exceeding $170K annually in the U.S. Growth opportunities include leadership positions, specialized architecture roles, and machine learning integration. With the right data engineer certification and a strong portfolio, you can accelerate this trajectory. The 365 Data Science Career Track provides both the technical training and data engineer credentials to help you move up faster.
What is the next role after data engineer?
The next step after data engineering often depends on your skills and career goals. Many move into senior-level positions, such as senior data engineer, data architect, or engineering manager. Others pivot toward specialized fields like machine learning engineering or analytics engineering. Advancing usually requires deeper expertise in system architecture, leadership skills, and broader business impact. Our data engineer career path includes advanced courses in cloud architecture, ETL optimization, and orchestration to prepare you for these higher-level roles.
Is a data engineer a good career?
Yes?data engineering offers excellent job security, competitive pay, and high demand across industries. As organizations generate and rely on more data, the need for skilled professionals who can design efficient pipelines and manage big data tools continues to grow. It?s a career with strong long-term potential, and with structured data engineer training, you can position yourself for success even without a computer science degree.
What is the roadmap for a data engineer?
A data engineer roadmap usually follows these stages: Learn programming (Python, SQL, Java) and database fundamentals. Gain skills in ETL, data modeling, and orchestration tools like Apache Airflow. Master big data frameworks such as Apache Spark and Snowflake. Develop cloud proficiency with AWS, Azure, or GCP. Build real-world projects and earn a data engineer certification. The 365 Data Science program is built exactly on this roadmap?offering step-by-step lessons, projects, and mentorship so you can progress from beginner to job-ready professional.
Is SQL enough for a data engineer?
SQL is essential for a data engineer, but it?s not enough on its own. You also need programming skills (Python, Java), experience with ETL processes, familiarity with big data tools like Apache Spark, and cloud knowledge (AWS, Azure, GCP). Our data engineer career path combines SQL mastery with these additional in-demand skills, ensuring you meet the real requirements found in thousands of 2025 job postings.
Which is the best course for a data engineer?
The best course covers both theory and practice?offering a complete data engineer roadmap with hands-on projects, big data tools, and cloud platforms. 365 Data Science?s Data Engineer Career Track is designed from real job market analysis, teaching SQL, Python, Apache Spark, Snowflake, Airflow, AWS, and more, while guiding you to build a portfolio and earn a data engineer certification.
Can you make $500,000 as a data engineer?
While $500,000 salaries are rare for most data engineers, senior positions at top tech companies?such as lead data architect, principal engineer, or director of data engineering?can reach total compensation in that range, especially when including bonuses and stock options. To reach those levels, you need years of experience, mastery of big data tools, and proven leadership skills. Following a professional data engineer career path and gaining recognized certifications can help you progress toward these elite roles. Explore 365 Data Science platform to see how a team of field experts can prepare you for the role.
How do I become a data engineer?
Becoming a data engineer typically involves: Learning SQL, Python, and database management. Mastering ETL processes, data modeling, and orchestration tools. Gaining cloud skills (AWS, Azure, or GCP). Building real-world projects and earning a data engineer certification. 365 Data Science?s Data Engineer Career Track provides all of these in one place?beginner-friendly lessons, expert-led projects, and a certification so you can enter the job market with confidence.
Can I learn data engineering in 3 months?
You can build a strong foundation in 3 months if you focus on essential skills like SQL, Python, and basic ETL processes. However, becoming fully job-ready as a data engineer usually takes 6?12 months of dedicated study, especially if you?re new to programming. The 365 Data Science data engineer training program is flexible, so you can accelerate your pace while still covering advanced topics like Apache Spark, Airflow, and AWS.
What?s required to begin a career as a data engineer?
To start a data engineer career, you?ll need: Basic programming knowledge (Python or SQL). Understanding of databases and data modeling. Willingness to learn big data tools and cloud platforms. Commitment to completing hands-on projects. The 365 Data Science Data Engineer Career Track gives you all of these?plus a recognized certification to validate your skills.
How can I start a career as a data engineer?
Start by following a structured data engineer roadmap: Learn SQL and Python. Master ETL and orchestration with tools like Apache Airflow. Build cloud skills (AWS, Azure). Complete real-world projects and get certified. Our Data Engineer Career Track covers each of these steps, helping you go from beginner to job-ready in under a year.
How long does it take to become a data engineer?
Most learners take 6?12 months to become job-ready, depending on prior experience. This includes mastering SQL, Python, big data frameworks, and cloud platforms, plus building a strong project portfolio. The 365 Data Science data engineer training program is self-paced, so you can progress faster or slower based on your schedule.
Are data engineer jobs in demand?
Yes?demand is very high. According to industry research, over 20,000 new data engineer jobs were created in the last year alone, with salaries averaging $120K?$160K. Companies across industries are investing in big data tools and need professionals who can build and manage robust data pipelines. Now is an ideal time to learn data engineering and enter the market.
How difficult is it to become a data engineer?
It can be challenging if you?re starting from zero, as it requires strong technical skills and continuous learning. However, with a guided curriculum, hands-on practice, and mentorship, it?s entirely achievable?even without a computer science degree. The 365 Data Science Data Engineer Career Track makes the process easier with a structured learning path, real-world projects, and a data engineer certification to help you stand out to employers.
