Master SQL, Python, ETL, cloud data, PySpark, Airflow, dbt, Docker, APIs, and modern data pipelines through a structured 10-month, project-based program.
Start from the foundations and progress step by step from databases and SQL to Python automation, ETL/ELT, cloud data, big data processing, pipeline orchestration, data quality, and a complete end-to-end Data Engineering capstone. No prior coding or IT background required.
Until You Get Hired. Resume, LinkedIn, mock interviews, and recruiter marketing until an offer is on the table.
Our graduates are trusted by hiring teams across the U.S.
Accenture
Cisco
You aren't just learning from an academic — you are training with a working Data Engineer who has spent over a decade building pipelines, dashboards, and analytics workflows in production environments.
Analytics & BI Instructor
With over a decade of experience, Fayek specializes in data engineering and analytics at top-tier companies like Veruna Inc. and OUTFRONT Media. His expertise lies in Python pipelines, SQL, and agile data workflows, consistently delivering impactful results. Passionate about mentoring, Fayek is dedicated to shaping the next generation of Data Engineers.
Connect on LinkedInThe curriculum starts with databases, SQL, Python, and data cleaning before progressing into Data Modeling, Cloud Data, PySpark, Airflow, dbt, APIs, Docker, Data Quality, and professional Data Engineering practices. Every month includes hands-on work and ends with a practical deliverable you can add to your portfolio.
Build the foundation every Data Engineer needs by understanding how business data is stored, organized, queried, and moved between systems.
Module 1 · Data Foundations
Module 2 · SQL & Databases
Learn Python for practical Data Engineering tasks and build your first complete automated ETL workflow.
Module 3 · Python Basics for Data
Module 4 · Data Cleaning & ETL
Learn how organizations structure analytics data and move modern Data Engineering workloads into cloud environments.
Module 5 · Data Modeling
Module 6 · Cloud Data Basics
Move beyond basic data processing and learn how larger datasets and automated production-style pipelines are handled.
Module 7 · Big Data & PySpark
Module 8 · Airflow & dbt
Bring everything together using APIs, Docker, Data Quality, professional Git workflows, and a complete end-to-end Data Engineering capstone.
Module 9 · APIs, Docker & Data Quality
Module 10 · Capstone & Career Preparation
Data Engineering is the process of collecting, cleaning, organizing, transforming, and moving data so businesses can use it for dashboards, analytics, reporting, automation, and AI. Think of Data Engineers as the people who build the roads that data travels on — making sure information moves reliably from files, applications, APIs, databases, and cloud systems into clean, structured environments that business teams can actually use. This beginner-friendly program is built for complete beginners, career changers from QA, IT support, operations, business, or analytics, and anyone targeting Data Engineering, ETL, SQL, Analytics Engineering, BI, Data Pipeline, or Cloud Data roles.
Design relational databases, organize business data, write analytical SQL queries, work with JOINs, aggregations, and build clean database structures.
Use Python to read, clean, process, transform, and move data while automating repetitive data tasks.
Extract data from files, APIs, and databases, transform it into usable formats, and load it into target systems.
Build fact tables, dimension tables, star schemas, and structured warehouse layers for analytics and reporting.
Understand cloud storage, cloud databases, data lakes, credentials, cost awareness, and modern cloud data environments.
Process datasets that have grown beyond traditional spreadsheet and pandas workflows using distributed processing.
Schedule, automate, monitor, and manage repeatable Data Engineering workflows using Airflow.
Build tested, documented, version-controlled transformations that convert raw warehouse data into business-ready models.
Build portable pipelines, extract live API data, add validation rules, logging, and automated data quality checks.
All real, industry-standard tooling — the same software modern data teams run, and the exact tools listed in U.S. Data Engineering job descriptions.
Our proven roadmap from your first free call to landing a Data Engineering role with a real paycheck.
Meet with experienced career advisors to discuss goals, create a personalized roadmap, and receive ongoing support throughout your journey.
Enroll easily online — sign agreements and receive access to lectures, lab practices, and class materials via our LMS.
Instructor-led classes on a fixed schedule: pre-class content plus live sessions, twice a week — theory first, then hands-on execution.
After training, participate in a 2–4 week internship with real teams for hands-on project experience.
Resume coaches help you bypass AI screening; interview prep covers technical screening and job market guidance.
Resume marketing and job placement through partnerships with 100+ staffing firms — we guide you through the entire search.
Free consultation · No enrollment fee · Placement support until hired
Throughout the program, you'll practice the same fundamental flow used by Data Engineering teams: Raw Data → Clean Data → Organized Data → Automated Pipeline → Business Use. Files, APIs and databases feed Python, pandas and PySpark; PostgreSQL, cloud storage and Data Lakes hold it; dbt transforms it; Airflow automates it; and Power BI, Tableau and analytics put it to work.
┌──(data㉿transfotech)-[~/etl-pipeline]
└─$ python etl_customer_pipeline.py
[extract] reading raw customer + sales files
[clean] removing duplicates and null records
[transform] calculating retention and revenue KPIs
[load] writing curated tables to warehouse
[validate] 24 quality checks passed
[publish] dashboard dataset refreshed Pipeline status: SUCCESS ✓
└─$ █
No previous coding or IT experience required. Start with the foundations and progress step by step.
Every month ends with a practical deliverable you can add to your portfolio.
Practice with SQL, Python, PySpark, Airflow, dbt, Docker, APIs, cloud technologies, and modern Data Engineering workflows.
Graduate with SQL projects, Python automation, ETL pipelines, Data Models, cloud projects, orchestration workflows, and a complete capstone.
The course prioritizes free, open-source, local, community-edition, and free-tier technologies wherever possible.
Build your résumé, LinkedIn profile, GitHub portfolio, technical interview skills, and final project presentation.
Verified Google reviews from students who transformed their careers at Transfotech Academy.
"I'm thoroughly impressed with Transfotech Academy's course curriculum — it's truly exceptional. The instructors are highly experienced and skilled, providing hands-on training that's invaluable. I'm extremely satisfied with my experience, and I often wish I had joined them earlier to kickstart my career in data engineering."
"The instructors here are knowledgeable and down-to-earth — they genuinely care about your future. It feels less like a school and more like a mentorship program."
"I started with zero knowledge. The team's honest approach, supportive instructors, and family-like treatment made the entire journey comfortable. I am now confidently job-ready."
"Their support team is outstanding and the constant job market updates they share kept me ahead of the curve throughout my job search. Highly recommend for newcomers."
"My success in IT is owed to Transfotech Academy. Before joining I wasn't sure about my career path. They provide hands-on training and job placement support that transformed me into a confident data engineering professional."
Our graduates build practical skills for Data Engineering, ETL, SQL, Analytics Engineering, BI, Data Pipeline, and Cloud Data roles across startups, enterprises, and modern digital teams.
"The hands-on labs and project-based curriculum gave me the edge I needed to land my first data analyst role."
"Real-world pipeline labs prepared me better than any certification course I've taken."
"From zero coding background to Analytics Engineer — the mentorship and placement support made all the difference."
"The SQL and data pipeline modules were unlike anything else out there. I referenced them in every interview."
Your final project brings together the complete Data Engineering lifecycle. Instead of finishing the program with only theoretical knowledge, you'll build an end-to-end Business Data Pipeline you can publish on GitHub and explain during interviews.
Collect data from files, REST APIs, or databases.
Fix missing values, duplicate records, formatting problems, and data quality issues.
Convert raw information into clean, structured, business-ready data.
Store processed data in a database or Data Warehouse.
Schedule the workflow so the pipeline can run repeatedly.
Publish documentation, create a dashboard, organize the GitHub repository, and present the final project.
One complete project. The full Data Engineering lifecycle.
The program develops technical skills relevant to entry-level Data Engineering and adjacent data roles. Estimated starting salary ranges (2026 market data):
Estimated 2026 United States salary ranges from the provided curriculum. Actual compensation varies based on location, company, industry, experience, and other factors.
End-to-end placement support from your first résumé edit to the day you start work.
Four flexible payment plans. No enrollment fee. No risk — job guarantee or 100% of your tuition back. Enroll within 15 days of the webinar for early-enrollment pricing.
3 × $1,600 / month · early enrollment
One-time payment · early enrollment (within 15 days of webinar)
6 × $850 / month · early enrollment
8 × $775 / month · early enrollment
Transfotech Academy
Certificate of Completion
Data Engineering Program: Pipelines & Cloud Data
Awarded to
Your Full Name
Every month builds toward a practical deliverable, so by graduation you leave with a working, end-to-end body of work — not just lecture notes. This is the portfolio and documentation you'll walk a hiring manager through, module by module.
Secure your spot now. Once seats fill up, enrollment closes until the next cohort — no exceptions.
⚠ Only 7 spots remaining — enrollment closes when capacity is reached
$500 tuition discount for this cohort only
1:1 session with a senior advisor before you start
First-access to 100+ hiring partner network
Free 20-min call · No commitment · Spot reserved after consultation
No. The program is designed to be beginner-friendly. You do not need previous coding experience, a Computer Science degree, or an IT background. The curriculum starts with Data Engineering fundamentals, databases, and SQL before gradually introducing Python and more advanced engineering tools.
The complete program runs for 10 months at approximately 4 hours per week, including live instructor-led learning, guided labs, assignments, and project work.
Yes. The program is project-based throughout. Each month combines concepts, guided lab work, and a practical deliverable that contributes to your Data Engineering portfolio.
You'll work with SQL, PostgreSQL, Python, pandas, NumPy, PySpark, Airflow, dbt, Docker, REST APIs, Git, GitHub, cloud storage, cloud databases, Data Lakes, Data Warehouses, Data Validation, and Power BI or Tableau.
You'll build a complete Business Data Pipeline that extracts data from files, APIs, or databases; cleans and transforms it; loads it into structured storage; automates the workflow; validates Data Quality; and presents the result through documentation, GitHub, and a dashboard.
The curriculum supports entry-level and adjacent roles including Junior Data Engineer, ETL Developer, SQL Developer, Analytics Engineer, BI Developer, Data Pipeline Developer, Junior Cloud Data Engineer, and Data Analyst with Engineering Skills.
While no ethical program "guarantees" a job, Transfotech Academy provides a highly structured path to employment: career counseling, interview preparation, portfolio building (GitHub/LinkedIn), and lifetime job support. This placement support is also available to international students.
Instructors dedicate approximately four to five hours per week to student support, including office hours and responsive communication through WhatsApp groups. All class recordings, learning materials, and syllabi are accessible through the LMS.
Transfotech is E-Verify certified through the USCIS, which means the organization is authorized to confirm the employment eligibility of its staff — a professional verification of the organization's standing regarding federal employment eligibility, distinct from traditional academic accreditation.
The cohort is led by Fayek Chowdhury, an Analytics & BI Instructor with over a decade of experience in data engineering and analytics at companies including Veruna Inc. and OUTFRONT Media. His expertise spans Python pipelines, SQL, and agile data workflows, and he is dedicated to mentoring the next generation of Data Engineers.
Build practical skills in SQL, Python, ETL, Cloud Data, PySpark, Airflow, dbt, Docker, APIs, Data Quality, and modern Data Pipelines through a beginner-friendly, project-based 10-month program. No pressure, no commitment — just 30 minutes with an advisor who will map out your path.
Free · 30 minutes · Placement support until hired · Next cohort starts soon