Overview
0.0
Contract - W2
Skills
Analytics
Data Warehouse
Amazon Web Services
Databricks
Snow Flake Schema
RDBMS
Oracle
Microsoft SQL Server
NoSQL
Database
MongoDB
Data Modeling
Data Engineering
Data Quality
Regulatory Compliance
Python
SQL
PySpark
Unstructured Data
Storage
Salesforce.com
ServiceNow
Oracle EBS
Cloud Computing
Genesys
Biometrics
IBM
GitHub
JIRA
Confluence
KPI
Data Integration
Web Services
Workflow
Statistics
Job Details
Role:Lead Data Engineer
Location:Hybrid 3 times a week in Roseland, NJ
Duration:12 month contract
Must haves:
AWS
Databricks
Lead experience- this can be supplemented for staff as well
Python
Pyspark
Contact Center Experience is a nice to have
TO SUCCEED IN THIS ROLE:
Ability to define and design complex data integration solutions with general direction and stakeholder access.
Capability to work independently and as part of a global, multi-faceted data warehousing and analytics team.
Advanced knowledge of cloud-based data engineering and data warehousing solutions, especially AWS, Databricks, and/or Snowflake.
Highly skilled in RDBMS platforms such as Oracle, SQLServer.
Familiarity with NoSQL DB platforms like MongoDB.
Understanding of data modeling and data engineering, including SQL and Python.
Strong understanding of data quality, compliance, governance and security.
Proficiency in languages such as Python, SQL, and PySpark.
Experience in building data ingestion pipelines for structured and unstructured data for storage and optimal retrieval.
Ability to design and develop scalable data pipelines.
Knowledge of cloud-based and on-prem contact center technologies such as Salesforce.com,
ServiceNow, Oracle CRM, Genesys Cloud, Genesys InfoMart, Calabrio Voice Recording, Nuance Voice Biometrics, IBM Chatbot, etc., is highly desirable.
Experience with code repository and project tools such as GitHub, JIRA, and Confluence.
Data Engineer Requirements:
Bachelor's degree in computer science, information technology, or a similar field.
8+ years of experience integrating and transforming contact center data into standard, consumption-
ready data sets incorporating standardized KPIs, supporting metrics, attributes, and enterprise hierarchies.
Expertise in designing and deploying data integration solutions using web services with client-driven workflows and subscription features.
Knowledge of mathematical foundations and statistical analysis.
Location:Hybrid 3 times a week in Roseland, NJ
Duration:12 month contract
Must haves:
AWS
Databricks
Lead experience- this can be supplemented for staff as well
Python
Pyspark
Contact Center Experience is a nice to have
TO SUCCEED IN THIS ROLE:
Ability to define and design complex data integration solutions with general direction and stakeholder access.
Capability to work independently and as part of a global, multi-faceted data warehousing and analytics team.
Advanced knowledge of cloud-based data engineering and data warehousing solutions, especially AWS, Databricks, and/or Snowflake.
Highly skilled in RDBMS platforms such as Oracle, SQLServer.
Familiarity with NoSQL DB platforms like MongoDB.
Understanding of data modeling and data engineering, including SQL and Python.
Strong understanding of data quality, compliance, governance and security.
Proficiency in languages such as Python, SQL, and PySpark.
Experience in building data ingestion pipelines for structured and unstructured data for storage and optimal retrieval.
Ability to design and develop scalable data pipelines.
Knowledge of cloud-based and on-prem contact center technologies such as Salesforce.com,
ServiceNow, Oracle CRM, Genesys Cloud, Genesys InfoMart, Calabrio Voice Recording, Nuance Voice Biometrics, IBM Chatbot, etc., is highly desirable.
Experience with code repository and project tools such as GitHub, JIRA, and Confluence.
Data Engineer Requirements:
Bachelor's degree in computer science, information technology, or a similar field.
8+ years of experience integrating and transforming contact center data into standard, consumption-
ready data sets incorporating standardized KPIs, supporting metrics, attributes, and enterprise hierarchies.
Expertise in designing and deploying data integration solutions using web services with client-driven workflows and subscription features.
Knowledge of mathematical foundations and statistical analysis.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.