Associate Data Engineer

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.
Associate 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 Associate Data Engineer, you will Design and Develop data pipelines and support the team in designing and solution complex data problems and follow 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.
Develop efficient data pipeline processes, warehouse architecture and business intelligence functions.
Work closely with other data engineers and analysts and align on engineering best practices.
Have 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
0-2 years of enterprise data engineering experience
Experience in 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
0-2 years of programming experience with command in Python and at least one or more of the following programming languages: SQL, Java, R or Spark
Skilled communicator, and demonstrate an ability to work with other Engineers, Product and end users
Experience with engineering best practices including CI/CD, code quality, testing, documentation, monitoring and more.
Good to have working experience within an agile scrum framework
Preferred Qualifications
Bachelor s degree in computer science, data science AND experience in business analytics, data science, software development, data modeling and/or data engineering work or masters 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
Experience working on AI/ML use-cases is a plus

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Role: Data Engineer
Industry Type: IT Services & Consulting
Department: Data Science & Analytics
Employment Type: Full Time, Permanent
Role Category: Data Science & Machine Learning

UG: Any Graduate
PG: Any Postgraduate