Staff Data Engineer

Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.

We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.

Summary:

The Genesys Data & Analytics Team

The Data & Analytics team is a central team comprised of Data Engineering, Data Platform/Technologies, Data Analytics, Data Science, Data Product, and Data Governance practices.  This mighty team serves the enterprise that includes sales, finance, marketing, customer success, product and more.  The team serves as a core conduit and partner to operational systems that run the business including Salesforce, Workday and more.  The Data Engineering team creates data products and consumption capabilities that meet the needs of our enterprise, analyst communities, and downstream systems that utilize data to drive the business.

Staff Data Engineer is a key member of the Data Engineering team and is part of Enterprise Data & Analytics organization that brings engineering excellence at design, deliver, and operate the capabilities that transforms our business.  As a Staff Data Engineer, you will lead complex data problems and influence other pod members on engineering best practices and standards. 

Responsibilities

Design, build and maintain batch or real-time data pipelines.

Partners closely with data architects to deliver in alignment with the long term architecture of data engineering solutions.

Work with product owners, data scientists and analysts to understand requirements, clean and integrate data, and determine the best way to provision that data.

Deliver to architectural design from principal engineers and architects on technology solutions that achieve results at scale.

Provide technical thought leadership for efficient data pipeline processes, warehouse architecture and business intelligence functions.

Guide, mentor and influence other data engineers and analysts on engineering best practices.

Drive a data operations mindset by monitoring and analyzing information to evaluate data pipeline performance & quality.

Collaborate with cross-function teams to design interfaces that support data integration (ingress and egress) with internal and external platforms.

Requirements

• 5-7 years of enterprise data engineering experience
• Proficiency with building enterprise grade data integration pipelines with optimization of data pipelines (AWS, Databricks, Snowflake)
• Experience with cloud database technologies such as Azure, Snowflake, Databricks, Google, AWS, Glue, Airflow, etc.
• Knowledge about data replication, data integration, and data masking
• 5-7 years of programming experience with command in Python and at least one or more of the following programming languages: SQL, Java, R or Spark
• Must be skilled communicator, and demonstrate an ability to work with end users and business leaders
• Experience with engineering best practices including CI/CD, code quality, testing, documentation, monitoring and more.
• Experience with distributed data processing
• Experience working within an agile scrum framework

Preferred Qualifications

• Bachelor’s degree in computer science, data science AND 5+ years of experience in business analytics, data science, software development, data modeling and/or data engineering work or master's degree in computer science
• Strong team player: ability to lead peers in accomplishment of common goals.
• Creative, innovative and solution design thinking: You evaluate things holistically and think through the objectives, impacts, best practices, and what will be simple and scalable

If a Genesys employee referred you, please use the link they sent you to apply.

About Genesys:

Genesys empowers more than 8,000 organizations in over 100 countries to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, Genesys delivers the future of CX to organizations of all sizes so they can provide empathetic, personalized experience at scale. As the trusted platform that is born in the cloud, Genesys Cloud helps organizations accelerate growth by enabling them to differentiate with the right customer experience at the right time, while driving stronger workforce engagement, efficiency and operational improvements. Visit www.genesys.com.

Reasonable Accommodations:

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 reach out to [email protected]. You can expect a response from someone within 24-48 hours. To ensure we set you up with the best reasonable accommodation, please provide them the following information: first and last name, country of residence, the job ID(s) or (titles) of the positions you would like to apply, and the specific reasonable accommodation(s) or modification(s) you are requesting.

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Genesys is an equal opportunity employer committed to equity 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.