Staff Software Engineer

Responsibilities

• Build data platforms and streaming engines that are real-time and batch in nature
• Optimize existing data platforms and infrastructure while exploring other technologies
• Provide technical leadership to the data engineering team on how data should be stored and processed more efficiently and quickly at scale
• Build and scale stream & batch processing platforms using the latest open-source technologies
• Work with data engineering teams and help with reference implementation for different use cases
• Improve existing tools to deliver value to the users of the platform
• Work with data engineers to create services that can ingest and supply data to and from external sources and ensure data quality and timeliness
  

Qualifications

• 8+ years of software development experience with at least 3+ years of experience on open-source big data technologies
• Knowledge of common design patterns used in Complex Event Processing
• Knowledge in Streaming technologies: Apache Kafka, Kafka Streams, KSQL, Spark, Spark Streaming
• Proficiency in Java, Scala
• Strong hands-on experience in SQL, Hive, Spark SQL, Data Modeling, Schema design.
• Experience and deep understanding of traditional, NoSQL and columnar databases
• Experience of building scalable infrastructure to support stream, batch and micro-batch data processing
• Experience utilizing Apache Iceberg as the backbone of a modern lakehouse architecture, supporting schema evolution, partitioning, and scalable data compaction across petabyte-scale datasets.
• Experience utilizing AWS Glue as a centralized data catalog to register and manage Iceberg tables, enabling seamless integration with real-time query engines and improving data discovery across distributed systems.
• Experience working with Druid/ StarRocks /Apache Pinot etc. , powering low-latency queries, routine Kafka ingestion, and fast joins across both historical and real-time data.