Senior Data Streaming Engineer
Core
Design and deliver a modern, real-time data platform supporting Infrastructure and ITSM domains by evolving legacy batch systems into a streaming-first ecosystem.
Role type
Senior IC data streaming engineer
Builds
Scalable, low-latency data pipelines and Iceberg-based data lakehouse tables
Domain
Financial services data engineering and real-time analytics
Deliverable
production ML models | product features
Required skills
Apache Flink, Confluent Kafka, Apache Iceberg, Python/Java/Scala, SQL, event-driven architecture, data modeling, CDC frameworks, RDBMS integration, Hadoop ecosystem
Preferred skills
Real-time analytics use cases, Kafka Connect, ksqlDB, data governance, cloud platforms (AWS/Azure/GCP), DevOps automation, Agile tools
Technologies
Apache Flink, Confluent Kafka, Apache Iceberg, Python, PySpark, Java, Scala, SQL, Parquet, Avro, ServiceNow, Hadoop, Spark, Hive, HDFS, Jira, Bitbucket
Responsibilities
Design and implement real-time data pipelines using Apache Flink and Confluent Kafka; Transform legacy batch and RDBMS-based data workflows into event-driven streaming architectures; Build and optimize streaming ingestion, transformation, and enrichment pipelines; Develop and maintain Iceberg-based data lakehouse tables; Ensure data quality, reconciliation, and consistency across streaming and batch systems; Optimize performance of streaming jobs including state management and checkpointing; Integrate data across multiple systems including ITSM platforms; Support CI/CD, deployment, and operational monitoring of streaming pipelines
Seniority
Senior, hands-on IC
