Senior Software Engineer, Data Platform
Role Overview
The Data Platform team builds foundational data services, systems, and products supporting streaming analytics, interactive reporting, and data and ML platforms.
The role designs, builds, and deploys systems powering analytics and machine learning, including high-volume, low-latency distributed data platform services.
The analytics infrastructure uses technologies including Kinesis, Flink, Elasticsearch, and Snowflake.
Key Skills for This Role
Full Job Posting
About the role
The Data Platform team builds foundational data services, systems, and products supporting streaming analytics, interactive reporting, and data and ML platforms.
The role designs, builds, and deploys systems powering analytics and machine learning, including high-volume, low-latency distributed data platform services.
The analytics infrastructure uses technologies including Kinesis, Flink, Elasticsearch, and Snowflake.
Responsibilities
- Design, implement, and own data-intensive, high-performance, scalable platform components.
- Collaborate with engineering teams, architects, and cross-functional partners on project development, design, and implementation.
- Conduct and participate in design reviews, code reviews, analysis, and performance tuning.
- Coach and mentor engineers; debug production issues across services and multiple levels of the stack.
- Design, build, deploy, and optimize streaming infrastructure and systems powering analytics and machine learning.
Required qualifications
- At least 4 years of software development experience.
- Proficiency in at least one language and comfort with more than one backend language; Java, TypeScript, Ruby, Go, and Python are examples.
- Experience with at least one of MySQL, Redis, or PostgreSQL.
- Demonstrable computer science fundamentals and strong API design skills.
- Comfort working with a geographically distributed team; ownership, accountability, attention to detail, and customer focus.
- Track record of delivering incrementally, gathering feedback, and iterating on solutions.
- Comfort with React or similar front-end UI stacks, or willingness to learn.
Preferred experience
- Cloud-based distributed computing technologies, including messaging systems such as Kinesis or Kafka; processing systems such as Flink, Spark, or Beam; storage and compute such as Snowflake or Hadoop; and coordinators or schedulers such as Kubernetes, Hadoop, or Mesos.
- Maintaining security, encryption, identity management, or authentication infrastructure; building mission-critical high-volume cloud services.
- Large-scale data integration in batch and online systems, including petabyte-scale environments; distributed systems experience such as Kafka or Hadoop.
Location eligibility
- The employee must be on U.S. soil, defined in the description as the 50 states, District of Columbia, or U.S. outlying areas. The posting states there is no citizenship requirement.
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