Big Data Engineer

🔍 United States, North Carolina, Durham, Durham

United States, Delaware, Dover, Virtual Office (Delaware) United States, Michigan, Lansing, Virtual Office (Michigan) United States, Missouri, Jefferson City, Virtual Office (Missouri) United States, North Carolina, Raleigh, Virtual Office (North Carolina) United States, Nebraska, Lincoln, Virtual Office (Nebraska) United States, Tennessee, Nashville, Virtual Office (Tennessee) United States, New Jersey, Trenton, Virtual Office (New Jersey) United States, Florida, Orlando, Virtual Office (Florida) United States, Idaho, Boise, Virtual Office (Idaho) United States, Indiana, Indianapolis, Virtual Office (Indiana) United States, Massachusetts, Boston, Virtual Office (Massachusetts) United States, Maine, Augusta, Virtual Office (Maine) United States, Maryland, Annapolis, Virtual Office (Maryland) United States, Minnesota, St Paul, Virtual Office (Minnesota) United States, Montana, Helena, Virtual Office (Montana) United States, Vermont, Montpelier, Virtual Office (Vermont) United States, New York, Albany, Virtual Office (New York) United States, North Dakota, Bismarck, Virtual Office (North Dakota) United States, Nevada, Washoe, Virtual Office (Nevada) United States, South Carolina, Columbia, Virtual Office (South Carolina) United States, Oregon, Salem, Virtual Office (Oregon) United States, Texas, Austin, Virtual Office (Texas) United States, Oklahoma, Oklahoma City, Virtual Office (Oklahoma) United States, Indiana, Indianapolis, Indianapolis United States, Arizona, Phoenix, Virtual Office (Arizona) United States, Wisconsin, Madison, Virtual Office (Wisconsin) United States, West Virginia, Charleston, Virtual Office (West Virginia) United States, Wyoming, Cheyenne, Virtual Office (Wyoming) United States, Kentucky, Frankfort, Virtual Office (Kentucky) United States, Arkansas, Little Rock, Virtual Office (Arkansas) United States, Virginia, Richmond, Virtual Office (Virginia) United States, South Dakota, Pierre, Virtual Office (South Dakota) United States, New Mexico, Santa Fe, Virtual Office (New Mexico) United States, Georgia, Atlanta, Virtual Office (Georgia) United States, Illinois, Chicago, Virtual Office (Illinois) United States, Rhode Island, Providence, Virtual Office (Rhode Island) United States, Louisiana, New Orleans, Virtual Office (Louisiana) United States, Utah, Salt Lake City, Virtual Office (Utah) United States, New Hampshire, Concord, Virtual Office (New Hampshire) United States, Alabama, Birmingham, Virtual Office (Alabama) United States, Ohio, Columbus, Virtual Office (Ohio) United States, Kansas, Topeka, Virtual Office (Kansas) United States, Connecticut, Hartford, Virtual Office (Connecticut) United States, Pennsylvania, Harrisburg, Virtual Office (Pennsylvania) United States, Iowa, Des Moines, Virtual Office (Iowa) United States, Mississippi, Jackson, Virtual Office (Mississippi)
Research and Development
210002ME Requisition #

The Genesys Cloud Analytics platform is the foundation on which decisions are made that directly impact our customer’s experience as well as their customers’ experiences. We are a data-driven company, handling tens of millions of events per day to answer questions for both our customers and the business. From new features to enable other development teams, to measuring performance across our customer-base, to offering insights directly to our end-users, we use our terabytes of data to move customer experience forward.
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.




Safety for our employees and our communities is a key priority for Genesys. We continue to experience rapid growth during the Covid-19 pandemic and are conducting remote hiring and onboarding processes. All hiring and onboarding processes are being conducted remotely at this time.

As our Covid-19 task force and internal teams plan to reopen our global offices, the policies and procedures will continue to be updated.


Reasonable Accommodations: 

Genesys is committed to providing an inclusive barrier-free environment, starting with the hiring process. If you require a reasonable accommodation to complete any part of the application process or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you or someone you know may complete the Reasonable Accommodations Form for assistance. Please use the Candidate field in the dropdown menu to ensure a timely response.  


This form is designed to assist job seekers who seek reasonable accommodation for the application process. Submissions entered for non-accommodation-related issues, such as following up on an application or submitting a resume, may not receive a response.  


About Genesys:

Every year, Genesys® orchestrates more than 70 billion remarkable customer experiences for organizations in more than 100 countries. Through the power of our cloud, digital and AI technologies, organizations can realize Experience as a Service℠, our vision for empathetic customer experiences at scale. With Genesys, organizations have the power to deliver proactive, predictive, and hyper personalized experiences to deepen their customer connection across every marketing, sales, and service moment on any channel, while also improving employee productivity and engagement. By transforming back-office technology to a modern revenue velocity engine Genesys enables true intimacy at scale to foster customer trust and loyalty. Visit


Genesys is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.


Please note that recruiters will never ask for sensitive personal or financial information during the application phase.

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