Staff Software Engineer, Data Platform

Responsibilities

• Design, implement and own data-intensive, high-performance, scalable platform components
• Work with engineering teams, architects and cross functional partners on the development of projects, design, and implementation
• Conduct and participate in design reviews, code reviews, analysis, and performance tuning
• Coach and mentor engineers to help scale up the engineering organization
• Debug production issues across services and multiple levels of the stack

Requirements

• 8+ years of experience in object-oriented language, preferably Java
• Hands-on experience using cloud-based distributed computing technologies including:
  • Messaging systems such as Kinesis, Kafka
  • Data processing systems like Flink, Spark, Beam
  • Storage & Compute systems such as Snowflake, Hadoop
  • Coordinators and schedulers like the ones in Kubernetes, Hadoop, Mesos
• Experience in developing and tuning highly scalable distributed systems
• Excellent grasp of software engineering principles
• Solid understanding of multithreading, garbage collection and memory management
• Experience with reliability engineering specifically in areas such as data quality, data observability and incident management
• Ability to access federal environments and/or have access to protected federal data (U.S. Person status required)

Nice-to-Haves

• Maintained security, encryption, identity management, or authentication infrastructure
• Leveraged major public cloud providers to build mission-critical, high volume services
• Hands-on experience in developing Data Integration applications for large scale (petabyte scale) environments with experience in both batch and online systems
• Contributed to the development of distributed systems or used one or more at high volume or criticality such as Kafka or Hadoop
• Experience developing Kubernetes based services on AWS Stack