Big Data Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

In this role, you’ll partner with software engineers, product managers, and data scientists to build and support a variety of analytical big data products. The best person will have a strong engineering background, not shy from the unknown, and will be able to articulate vague requirements into something real. We are a team whose focus is to operationalize big data products and curate high-value datasets for the wider organization as well as to build tools and services to expand the scope of and improve the reliability of the data platform as our usage continues to grow on a daily basis.
 
What you will be doing:

• Working with team members to build the next generation Genesys Cloud data and analytics platform.
• 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 as well as evangelize best practices.
• 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.

Skills we are looking for:

• Experience working with Airflow for orchestration
• Experience working with Apache Spark on EMR for batch processing
• Expertise in Java, Python or similar programming languages

Technologies we use (and will teach you to 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. This usually translates to Java for developing services and applications and Python for tooling.
• Packer and ansible for immutable machine images.
• AWS for cloud infrastructure.
• Infrastructure (and everything, really) as code.
• Automation for everything. CI/CD, testing, scaling, healing, etc.
• DynamoDB and S3 for query and storage.

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 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 familiarity with AWS or other Cloud technologies.
• You have engineered scalable software using big data technologies (e.g. Hadoop, Spark, Hive, Presto, Elasticsearch, Druid, etc). 
• You have some experience building data pipelines (real-time or batch) on large complex datasets.
• You have managed and supported ETL pipeline infrastructure.
• You have monitored and improved ETL pipeline performance.