Description

You will design, build, and maintain scalable data platforms and pipelines, ensuring system reliability and performance at scale.

This role is on-site.

Responsibilities

• Architect distributed computing solutions using Apache Spark or Ray for massive-scale parallel data processing.
• Design and implement real-time streaming pipelines using Kafka, Kinesis, or Flink.
• Write high-performance SQL for metrics computation, window functions, and query tuning across relational and columnar databases.
• Develop reusable pipeline code in Python or Scala and interact with APIs.
• Orchestrate data workflows using Directed Acyclic Graphs (DAGs) in tools like Apache Airflow or Prefect.

Required Skills

• 5+ years of experience in data engineering or related field.
• Proficiency in Python, Java, PySpark, and SQL.
• Experience with AWS cloud infrastructure, including storage/compute decoupling and cost optimization.
• Hands-on experience with Kafka for event-driven architecture.
• Familiarity with Snowflake, Redshift, or BigQuery.
• Knowledge of Docker for containerization and deployment.
• Bachelor's degree in Computer Science or related field.

Key Skills

Education

Bachelor's degree