Job
Description
What You’ll Do Designs and delivers high traffic, high performance solutions to provide enriched data back to engineering systems Define the egress strategies and architectures to expose analytical data from the public cloud Collaborate with the stakeholders and engineering partners to define the architecture and implement solutions Act as a subject matter expert for technical guidance, solution design and best practice Develop scalable solutions to implement REST and utilize GraphQL and API Gateways to provide user friendly interfaces Develop streaming data pipelines for custom ingestion, processing and egress to the public cloud Design and implementation of Kafka / PubSub services to publish events adhering to Catalog messaging standards Develop containerized solutions, CI/CD pipelines and utilize orchestration services like Kubernetes Define key metrics, troubleshoot logs using Datadog, APM, Kibana, Grafana, Stackdriver etc Manage and mentor associates; ensure the team is being challenged, exposed to new opportunities, and learning, while still being able to deliver on ambitious goals Develop a technical center of excellence within the analytics organization through training, mentorship, and process innovation Build, lead, and mentor a team of highly talented data professionals working with petabyte scale datasets and rigorous SLAs What You’ll Need A graduate of a computer science, mathematics, engineering, physical science related degree program with 6+ years of relevant industry experience 6+ years of programming experience with at least one language such as Python, Go, Java Script, React JS. Experience in leading design and implementation of medium to large-scale complex projects Experience building high performance, scalable and fault-tolerant services and applications Experience with service oriented architecture (REST & GraphQL) and ability to architect scalable microservices Experience with web frameworks like Django, FastApi, Flask, Spring, Grail, Struts Experience in NoSQL solutions (MongoDB, Hbase/BigTable, Aerospike) and caching technologies (Redis, Memcache) Experience building big data pipelines using cloud-computing technologies preferred Experienced developing in cloud platforms such as Google Cloud Platform (preferred), AWS, Azure, or Snowflake at scale Experience with real-time data streaming tools like Kafka, Kinesis, PubSub, Apache Storm or any similar tools Experience with Docker containers and Kubernetes orchestration Experience in unit testing frameworks, CI/CD implementation (Buildkite preferred) Experience with monitoring and logging tools like Datadog, Grafana, Kibana, Splunk, Stackdriver etc Show more Show less
