Junior Python And Apache Kafka Real-Time Data Pipeline Engineer

What role will you play in the team

You will play a pivotal role in designing, constructing, and maintaining robust real-time data streaming architectures. As a core member of our data engineering unit, you will collaborate closely with machine learning architects and database administrators to ensure seamless ingestion, processing, and delivery of high-throughput data streams supporting enterprise analytics platforms.

What you will do

Your daily routine will involve writing optimized Python code, configuring Apache Kafka message brokers, and developing scalable ETL pipelines. You will monitor streaming latencies, troubleshoot distributed cluster bottlenecks, and implement data quality validation checks to guarantee uninterrupted data flow across multi-cloud environments.

Key responsibility

• Develop and maintain scalable data ingestion pipelines utilizing Python and Apache Kafka for real-time analytics.
• Design, construct, and optimize ETL workflows using modern data integration tools and custom scripts.
• Monitor streaming infrastructure performance, resolve latency issues, and scale clusters to accommodate high data volumes.
• Implement stringent data validation protocols and schema registries to maintain stream integrity.
• Collaborate with cross-functional teams to integrate streaming data outputs into downstream machine learning models and dashboard platforms.

Required Qualification and Skills

• Bachelor's degree in Computer Science, Information Technology, or a related quantitative discipline.
• Minimum 0 to 1 years of hands-on professional experience in Python development and data pipeline construction.
• Proficiency in streaming technologies specifically Apache Kafka, Zookeeper, and event-driven architecture design.
• Working knowledge of relational and NoSQL databases including PostgreSQL, MySQL, and MongoDB.
• Strong understanding of data warehousing concepts, SQL querying, and distributed computing principles.

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Benefits Included

• Comprehensive health insurance coverage for employees and their immediate family members.
• Flexible working hours and structured remote work options during designated periods.
• Annual professional development allowance for technical certifications and conference attendance.
• Generous paid time off and wellness leave policies to ensure healthy work-life balance.
• Regular team building events, hackathons, and collaborative innovation workshops.

A Day in the Life

Your day begins by reviewing real-time monitoring dashboards to assess stream health across active Kafka topics. You spend the morning optimizing a Python-based data transformation script to reduce processing lag. Post-lunch, you collaborate with the analytics squad to design a new ingestion schema for an upcoming client deployment, followed by code reviews and infrastructure tuning.