We are looking for a Big Data Engineer with strong experience in building large-scale distributed data processing systems, data engineering solutions, or high-performance internet-scale applications. The ideal candidate is passionate about solving complex data challenges, optimizing performance, and delivering scalable, reliable systems.

Key Responsibilities:

• Design, develop, and maintain large-scale distributed data processing pipelines and applications.
• Build and optimize data engineering solutions to support analytics, reporting, and real-time data needs.
• Work with big data technologies, cloud platforms, and distributed systems to ensure high availability and scalability.
• Collaborate with cross-functional teams including Data Scientists, Software Engineers, and Product Managers.
• Ensure data quality, integrity, and security across the ecosystem.
• Troubleshoot and resolve performance bottlenecks in large-scale data applications.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Strong experience with large-scale distributed data systems (e.g., Hadoop, Spark, Flink, Kafka, Hive, Presto, etc.).
• Expertise in data engineering, ETL pipelines, and data warehousing concepts.
• Solid programming skills in Java, Scala, or Python.
• Experience with cloud platforms (AWS, GCP, Azure) for big data processing.
• Strong understanding of distributed systems, algorithms, and performance optimization.
• Proven track record of building and scaling internet-scale applications or data platforms.

Preferred Skills (Good to Have):

• Knowledge of real-time streaming systems.
• Familiarity with containerization & orchestration (Docker, Kubernetes).
• Hands-on experience with machine learning pipelines or analytics platforms.
• Strong problem-solving and communication skills.