Description

You will lead end-to-end development of high-quality data solutions, architecting systems for large-scale data volumes and transaction processing.

This role is on-site.

Responsibilities

• Build and manage large-scale data pipelines for high-volume, multi-dimensional data and machine learning models.
• Design and optimize systems for high-throughput data ingestion and low-latency querying.
• Implement real-time streaming solutions and manage data scheduling workflows.
• Integrate data solutions into existing systems by collaborating with cross-functional engineering teams.

Required Skills

• 5+ years of experience in Big Data engineering and system design.
• Hands-on expertise in SQL and one or more languages: Java, Scala, or Python.
• Proficiency with Hadoop, Spark, Hive, and Kafka.
• Experience with real-time streaming platforms such as Flink, Spark Streaming, and Pinot.
• Working knowledge of NoSQL databases including ClickHouse, MongoDB, Cassandra, HBase, and Redis.
• Experience with scheduling tools like Airflow and Control-M.
• Practical use of Docker and Kubernetes for container orchestration.
• Familiarity with Agile development and CI/CD workflows.

Key Skills

Education

Any Gradute