Data Pipeline Engineer (Kafka)
Profile Code: AL-ML-04
- ₹17 LPA (Median Salary)
- Lecture Duration 2hrs
- Course Duration 12 Weeks
Skills You Learn: Apache Kafka & Event Streaming | Real-Time Data Pipeline Development | Distributed Systems & Messaging Architecture | ETL & Data Integration | Stream Processing (Spark Streaming, Flink) | SQL, Python & Java | Cloud Data Engineering & DevOps | Performance Tuning & Data Reliability
Overview Video

About This Course
Data Pipeline Engineers (Kafka) design, build, and manage high-performance data streaming pipelines that enable real-time data processing across enterprise applications. They work with data engineers, software developers, and analytics teams to develop scalable, fault-tolerant data integration solutions using event-driven architectures. This course prepares learners for a career as a Data Pipeline Engineer (Kafka) through hands-on projects, industry workflows, collaborative learning, and real-world case studies aligned with current hiring expectations in India. Learners gain expertise in Apache Kafka, Python, SQL, stream processing, event-driven architecture, data ingestion, ETL pipelines, Kafka Connect, Kafka Streams, monitoring, and cloud-based data platforms. The curriculum includes practical experience with industry-standard big data and messaging technologies. Through live projects and capstone assignments, participants develop programming, analytical, and data engineering skills, preparing them for Data Pipeline Engineer, Kafka Developer, Streaming Data Engineer, Big Data Engineer, and Data Integration Engineer roles across diverse industries.
Key Responsibilities
- Design and develop real-time data pipelines using Apache Kafka and streaming technologies
- Build, manage, and optimize data ingestion and event-driven architectures
- Develop ETL and data processing workflows for high-volume data streams
- Monitor pipeline performance, scalability, and data reliability across distributed systems
- Collaborate with data engineers, data scientists, and application teams to enable real-time analytics and machine learning applications.
Growth Path
Tools Used
Perfect For
Computer Science and Engineering Graduates | Software Developers and Backend Engineers | Data Engineering and Big Data Professionals | Cloud and Distributed Systems Enthusiasts | Machine Learning and Analytics Aspirants | Individuals Interested in Real-Time Data Processing and Scalable Data Architectures
Fee Structure
Mentor
Analytics Learners
Professional Analyst & Mentor
Explore Various Career Paths in Machine Learning & Data Science
Related analyst roles inside the same industry.


