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Data Engineer Experience: 5-8 Years Location: Remote Responsibilities: • Develop, implement, and maintain the information data lake and using insight platforms to enable decision support systems for the overall organization. Partner with the business and our customers to understand their data and reporting requirements. • Bring data sets together to answer business questions and drive growth. Design ETLs to ingest the data into the data warehouse and data lake, as well as end-user facing reporting applications. • Collaborate with business customers and development teams to define requirements and deliver flexible, scalable, end-to-end solutions. • Work with new technologies while driving business intelligence solutions end-to-end: business requirements, data modelling, ETL, metadata, reporting, and dashboarding. • Apply expertise in the design, creation, management, and business use of large datasets. • Defines SLA for all areas of ownership. • Experience with Data modelling, SQL, ETL, Data Warehousing and Data lakes • Experience in writing SQL and Python scripts • Experience in building dashboards and report using Microsoft Power BI Preferred Qualifications: • Experience in transforming data using Azure data factory • Experience working with Spark and Azure Databricks • Ability to balance and prioritize multiple conflicting requirements with high attention to detail. • Strong verbal/written communication & data presentation skills, including ability to succinctly summarize key findings and effectively communicate with both business and technical teams. • Familiarity of scripting language such as Python, PySpark, or JavaScript • Knowledge of Azure Databricks and MPP databases • Experience with Data Lake development • Exposure to NoSQL databases (such as Cosmos DB, MongoDB) • Experience working on Microsoft Power BI dashboards. • Experience following the Agile processes. • Experience working with distributed version control system like Git. • Experience with Mulesoft/Kingswaysoft/Marketo.
Job Responsibility
Develop, implement, and maintain the information data lake and using insight platforms to enable decision support systems for the overall organization
Partner with the business and our customers to understand their data and reporting requirements
Bring data sets together to answer business questions and drive growth
Design ETLs to ingest the data into the data warehouse and data lake, as well as end-user facing reporting applications
Collaborate with business customers and development teams to define requirements and deliver flexible, scalable, end-to-end solutions
Work with new technologies while driving business intelligence solutions end-to-end: business requirements, data modelling, ETL, metadata, reporting, and dashboarding
Apply expertise in the design, creation, management, and business use of large datasets
Defines SLA for all areas of ownership
Requirements
Data Engineer
Experience: 5-8 Years
Experience with Data modelling, SQL, ETL, Data Warehousing and Data lakes
Experience in writing SQL and Python scripts
Experience in building dashboards and report using Microsoft Power BI
Nice to have
Experience in transforming data using Azure data factory
Experience working with Spark and Azure Databricks
Ability to balance and prioritize multiple conflicting requirements with high attention to detail
Strong verbal/written communication & data presentation skills
Familiarity of scripting language such as Python, PySpark, or JavaScript
Knowledge of Azure Databricks and MPP databases
Experience with Data Lake development
Exposure to NoSQL databases (such as Cosmos DB, MongoDB)
Experience working on Microsoft Power BI dashboards
Experience following the Agile processes
Experience working with distributed version control system like Git