• Location: Atlanta, Georgia
  • Date Posted: 24th Apr, 2020
  • Reference: 4242020AG

Core Requirements: Bachelor's degree in Computer Science, Industrial Engineering, BusinessAnalytics, or equivalent. 5+ years of broad-based IT experience with technical knowledge of data Integration (ETL ,ELT) technologies and approaches, Data Warehousing, Data Lake Methodologies. Should have knowledge and skills with tools such as Microsoft Azure,SQL data warehouse,PolyBase, Visual Studio, AzureSQL DB,SQL Server 2012 to 2019 Strong T-SQL Development and performance tuning skills Performance tuning ofSQL,SSIS andADF solutions.

Strong Knowledge of cloud concepts such as IaaS, PaaS and Saas. Strong Knowledge of design and administration of SSIS and SQL Agent Ability to troubleshoot and maintain existing SSAS (Multidimensional and Data Mining Models) when necessary Ability to troubleshoot and maintain existing SSRS solutions when necessary. Knowledge and experience in prototyping, designing, and requirement analysis Knowledge and experience in Estimation, Agile Methodology, and Source control Strong Azure Data skills.

Must have: Azure SQL DB, Azure Data Factory V2

Nice to have: Azure Synapse (Formerly Azure SQL DW), Azure Data Bricks, Azure Analysis Services, Azure Data Lake Data Integration tools in heavy use at Rentpath include SSIS , Azure Data Factory v2, and Azure Data Bricks.

Knowledge of any of the following bonus: Oracle PL-SQL, Power BI, Tableau, Kafka, Hive, Github, Google Big Query and Google Analytics.

Roles & Responsibilities will include: Designing , developing and deploying Data Integration (ETL and or ELT) solutions using agreed upon design patterns and technologies, working with a large variety of data sources from json, csv, Oracle, SQL Server, Azure Synapse, Azure Analysis Services, Azure SQL DB, DataLake, polybase and Streaming data sets. Creating workflows, templates, and design patterns. Communicating with stakeholders to obtain accurate business requirements Creating and performing unit tests for solutions. Converting existing SSIS packages into Azure Data Factory Pipelines.