Staff Software Engineer

The Streaming Data Platform team is responsible for building, managing complex stream processing topologies using the latest open-source tech stack, build metrics and visualizations on the generated streams and create varied data sets for different forms of consumption and access patterns. We're looking for a seasoned Staff Software engineer to help us build and scale the next generation of streaming platforms and infrastructure at Fanatics Commerce.

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.