Data Engineer Roadmap: Zero to Job-Ready
Follow this data engineer roadmap from zero to job-ready: Python, SQL, data modeling, Airflow, dbt, Spark, streaming, and cloud data platforms.
0 / 20 modules
Your recommended path
- Start at Programming Foundations. Learn Python and SQL first, and everything else second.
- Data Engineers build the pipelines that move and clean data. Data Analysts turn that data into reports, and Data Scientists build models on it. This roadmap is for the builders.
- Do not jump ahead to Spark or Kafka before you are comfortable writing Python scripts and SQL queries.
- Budget 12 to 18 months of consistent study. One to two hours a day is enough, as long as you do every hands-on lab instead of just reading.
- You can skip these for now: Hadoop MapReduce, Scala, Flink internals, and data mesh.
- By the end of the required Capstone projects, you will be ready for junior to mid-level data engineering roles. Seniority beyond that comes from production experience, which this roadmap prepares you for.
Your recommended path
- You already have programming or SQL fundamentals, so start at Data Modeling and Databases.
- Spend extra time on pipeline orchestration and cloud platforms. These are the biggest gaps for analysts and developers.
- Budget 6 to 9 months from this entry point, and build 2 to 3 portfolio projects before applying.
Your recommended path
- Your infrastructure skills transfer well: you already understand cloud, containers, and CI/CD. Start at Data Modeling and Databases, because your gap is data-specific thinking, not infrastructure.
- Pay extra attention to streaming pipelines and data quality. These are where data engineering differs most from DevOps.
- Budget 4 to 6 months from this entry point.
Your recommended path
* Use this roadmap as a gap analysis to find what you have not formally studied. * The Advanced steps, especially streaming and data quality at scale, are where most working data engineers have gaps. * The required Capstone projects give you portfolio evidence for senior and lead roles.
Steps in this roadmap
Status Module Topics Learn Quiz Resources Save Python for Data Engineering 11 Read +1 SQL for Data Engineering 18 Read Git and GitHub 12 Read +1 Linux for DevOps 37 Read Shell Scripting Tutorial: Bash for DevOps 14 Read Status Module Topics Learn Quiz Resources Save Data Modeling for Data Engineers 13 Read Data Warehouse Design and Query Performance 13 Read +1 Status Module Topics Learn Quiz Resources Save Cloud Platforms for Data Engineers 13 Read +1 Status Module Topics Learn Quiz Resources Save Docker for Data Engineers 13 Read ETL Pipelines with Apache Airflow 13 Read Status Module Topics Learn Quiz Resources Save Analytics Engineering with dbt 12 Read Status Module Topics Learn Quiz Resources Save Apache Spark for Batch Processing 13 Read Status Module Topics Learn Quiz Resources Save Modern Data Warehousing and the Lakehouse 9 Read +1 Status Module Topics Learn Quiz Resources Save Apache Kafka for Data Engineers 12 Read +1 Real-Time Stream Processing with Apache Flink 14 Read Status Module Topics Learn Quiz Resources Save Data Quality with Great Expectations 13 Read Data Governance and Catalog 13 Read CI/CD and Testing for Data Pipelines 8 Read Status Module Topics Learn Quiz Resources Save Advanced Specialisations for Data Engineers 12 Read Status Module Topics Learn Quiz Resources Save Data Engineering Capstone and Interview Preparation 13 Read
Final assessment
Complete every step in this roadmap to unlock the final assessment.
Salary outcomes
- Junior Data Engineer
- ₹4L - ₹9L
- Data Engineer
- ₹9L - ₹20L
- Senior Data Engineer
- ₹20L - ₹40L
- Lead / Staff Data Engineer
- ₹40L - ₹70L
Explore other roadmaps
Frequently asked questions
11 steps and 20 modules, in order: Beginner (Programming Foundations and Data Modeling and Databases); Intermediate (Cloud Platforms for Data Engineers, Data Pipelines and ETL with Airflow, Analytics Engineering with dbt and Batch Processing with Apache Spark); Advanced (Modern Data Warehousing and the Lakehouse, Streaming Data Engineering, Data Quality and Governance and Specialisation - Choose Your Direction); Capstone (Capstone - Data Engineering Portfolio).
Yes. Every step and module of the Data Engineer Roadmap: Zero to Job-Ready roadmap is free to read on DevOps Network with no paywall. A free account lets you track progress, save modules and take the quizzes.
Pick the learning path closest to your background (I'm New to Tech, I'm a Developer or Analyst Moving into Data Engineering, I'm in Cloud or DevOps, Adding Data Skills and I'm Already Working with Data Tools) at the top of the page. The step list then shows only the steps on that path; "All steps" brings the rest back.
Work through the step's modules, then pass its quiz. The quiz unlocks once the required modules are done, and passing it marks the step complete. You can also practise any quiz without the lock in the practice hub.
Yes. A final assessment unlocks after you complete all 11 steps and tests everything across the roadmap.
Typical ranges listed for this path: Junior Data Engineer: ₹4L - ₹9L; Data Engineer: ₹9L - ₹20L; Senior Data Engineer: ₹20L - ₹40L; Lead / Staff Data Engineer: ₹40L - ₹70L. Actual offers vary by company, city and experience.