Summary:
Develop and deploy highly available, fault-tolerant software that will help drive improvements towards the features, reliability, performance, and efficiency of the Genesys Cloud Analytics platform.
Actively review code, mentor, and provide peer feedback.
Collaborate with engineering teams to identify and resolve pain points and proselytize best practices.
Partner with various teams to transform concepts into requirements and requirements into services and tools.
Engineer efficient, adaptable and scalable architecture for all stages of data lifecycle (ingest, streaming, structured and unstructured storage, search, aggregation) in support of a variety of data applications.
Build abstractions and re-usable developer tooling to allow other engineers to quickly build streaming/batch self-service pipelines.
Build, deploy, maintain, and automate large global deployments in AWS.
Troubleshoot production issues and come up with solutions as required.
This may be the perfect job for you if:
You have a strong engineering background with ability to design software systems from the ground up.
You have expertise in Java. Python and other object-oriented languages are a plus.
You have experience in web-scale data and large-scale distributed systems, ideally on cloud infrastructure.
You have a product mindset. You are energized by building things that will be heavily used.
You have engineered scalable software using big data technologies (e.g., Hadoop, Spark, Hive, Presto, Elasticsearch, etc).
You have experience building data pipelines (real-time or batch) on large complex datasets.
You have worked on and understand messaging/queueing/stream processing systems.
You design not just with a mind for solving a problem, but also with maintainability, testability, monitorability, and automation as top concerns.
Technologies we use and practices we hold dear:
Right tool for the right job over we-always-did-it-this-way.
We pick the language and frameworks best suited for specific problems.
Packer and Ansible for immutable machine images.
AWS for cloud infrastructure.
Automation for everything. CI/CD, testing, scaling, healing, etc.
Hadoop, Hive, and Spark for batch.
Airflow for orchestration.
Dynamo, Elasticsearch, Presto, and S3 for query and storage.
About Genesys
Every year, Genesys®delivers more than 70 billion remarkable customer experiences for organizations in over 100 countries. Through the power of the cloud and AI, our technology connects every customer moment across marketing, sales and service on any channel, while also improving employee experiences. Genesys pioneered Experience as a Service so organizations of any size can provide true personalization at scale, interact with empathy, and foster customer trust and loyalty. This is enabled by Genesys Cloud™, an all-in-one solution and theworld’s leading public cloud contact center platform,designed for rapid innovation, scalability and flexibility. Visit www.genesys.com.
Genesys is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.