Principal PS Consultant

Genesys

About The Position

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. Genesys employs more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. While offering great benefits and perks like larger tech companies, employees have the independence to make a larger impact on the company and take ownership of their work. The Principal PS Consultant will interface with business customers, gathering and understanding requirements. They will interface with customer and Genesys data science teams in discovery, extraction, loading, data transformation, and analysis of results. The role involves defining and utilizing a data intuition process to cleanse and verify the integrity of customer & Genesys data for analysis, and implementing, owning, and improving data pipelines using best practices in data modeling, ETL/ELT processes. The consultant will build, improve, and provide ongoing optimization of high-quality models, and work with PS & Engineering to deliver specific customer requirements and report back customer feedback, issues, and feature requests. Continuous improvement in reporting, analysis, and overall process is expected, along with visualizing, presenting, and demonstrating findings as required. The position also includes performing knowledge transfer to customer and internal teams, and communicating within the global community respecting cultural, language, and time zone variations, demonstrating flexibility to adjust working hours to match customer and team interactions.

Requirements

Bachelor’s / Master’s degree in quantitative field (e.g., Computer Science, Statistics, Engineering)
8+ years of relevant experience in Data Science or Data Engineering
8+ years of hands-on experience in Elasticsearch, Kibana, and real-time analytics solution development
Good working knowledge on any programming language like Java, NodeJS,Python.
Expertise with data modeling, data warehousing, and ETL/ELT development
Proficiency with REST API, JSON, AWS
Experience in working and delivering projects independently.
Ability to multi-task and context switch between projects and tasks
Curiosity, passion, and drive for data queries, analysis, quality, and models
Excellent communication, initiative, and coordination skills with great attention to detail.
Ability to explain and discuss complex topics with both experts and business leaders.

Nice To Haves

Hands-on application development experience in AWS/Azure/GCP and it is good to have experience in Snowflake, Tableau, or ELK
Application development background of using any contact center product suites such as Genesys, Avaya, Cisco etc. is an added advantage
Hands on Experience with JavaScript , Node.JS or Python
Hands experience with AWS Application development, (Lambda, ECS Fargate, EKS, Docker , SQS, etc..)

Responsibilities

Interface with business customers, gathering and understanding requirements.
Interface with customer and Genesys data science teams in discovery, extraction, loading, data transformation, and analysis of results.
Define and utilize data intuition process to cleanse and verify the integrity of customer & Genesys data to be used for analysis.
Implement, own, and improve data pipelines using best practices in data modeling, ETL/ELT processes.
Build, improve, and provide ongoing optimization of high-quality models.
Work with PS & Engineering to deliver specific customer requirements and report back customer feedback, issues, and feature requests.
Continuous improvement in reporting, analysis, and overall process.
Visualize, present, and demonstrate findings as required.
Perform knowledge transfer to customer and internal teams.
Communicate within the global community respecting cultural, language, and time zone variations.
Demonstrate flexibility to adjust working hours to match customer and team interactions.