Data Engineer Roadmap
Build scalable data pipelines and infrastructure
About This Roadmap
Data Engineering is the backbone of modern data-driven organizations, focusing on building and maintaining the infrastructure that enables data collection, storage, and processing at scale. As a data engineer, you will design and implement data pipelines, manage databases, work with big data technologies, and ensure data quality and availability. This comprehensive roadmap covers SQL and NoSQL databases, ETL/ELT processes, data warehousing, big data tools like Spark and Kafka, cloud platforms, and orchestration tools like Airflow. You will learn to handle petabytes of data, optimize query performance, and build real-time data streaming systems. Data engineers are in extremely high demand as companies increasingly rely on data for decision-making. The role requires strong programming skills, understanding of distributed systems, database expertise, and knowledge of cloud infrastructure.
Prerequisites
- Programming knowledge (Python/Java)
- SQL basics
- Understanding of databases
- Linux fundamentals
What You'll Learn
Complete Learning Path
8-10 weeks
1Python Advanced
OOP, error handling, file I/O, libraries
2SQL Mastery
Complex queries, optimization, indexing, transactions
3PostgreSQL
Administration, performance tuning, replication
4NoSQL
MongoDB, Redis, Cassandra, use cases
6-8 weeks
1Relational Modeling
Normalization, ER diagrams, foreign keys
2Dimensional Modeling
Star schema, snowflake schema, fact tables
3Data Warehousing
OLAP vs OLTP, data marts, slowly changing dimensions
4Data Lakes
Architecture, storage formats (Parquet, Avro)
8-10 weeks
1ETL Fundamentals
Extract, transform, load processes
2Apache Airflow
DAGs, operators, scheduling, monitoring
3Data Quality
Validation, testing, monitoring
4Version Control
Git, CI/CD for data pipelines
10-12 weeks
1Apache Spark
RDDs, DataFrames, PySpark, optimization
2Hadoop Ecosystem
HDFS, MapReduce, Hive, HBase
3Stream Processing
Apache Kafka, real-time pipelines
4Data Formats
Parquet, ORC, Avro, compression
8-10 weeks
1AWS
S3, Redshift, Glue, EMR, Lambda
2GCP
BigQuery, Dataflow, Pub/Sub, Cloud Storage
3Azure
Synapse, Data Factory, Databricks
4Infrastructure as Code
Terraform, CloudFormation
6-8 weeks
1Data Governance
Security, compliance, lineage, cataloging
2Performance Optimization
Query tuning, partitioning, caching
3Real-time Analytics
Lambda architecture, Kappa architecture
4DataOps
Automation, monitoring, observability
Tools & Technologies
Career Opportunities
- Data Engineer
- Big Data Engineer
- ETL Developer
- Data Platform Engineer
- Analytics Engineer
- Data Architect