ShiftCode Analytics
Azure Databricks certified engineer - Con Edison
ShiftCode Analytics, New York, New York, us, 10261
Interview: Onsite
Hybrid: NYC, NY (need local)
Visa: USC, GC and GC EAD
MUST SHOW PROOF OF ADDRESS
MUST PROVIDE LINKED IN PROFILE
MUST BE ABLE TO DO A 30 MINUTE TECHNICAL ROUND WITH MY TECH SCREENER BEFORE SUBMITTING TO CLIENT
Need a Short video to submit the client stating the following:
Hi, my name is and I am applying for the Sr. Cloud Engineer role with Client and I am open to doing an in person interview, relocating and working in a hybrid capacity , thank you.
JD: Must Have:
Ability to intrepid, modify and write scripts and SQL queries Azure Cloud Data Engineer Azure Databricks Azure Data Factory
PowerBI Report Server Python
Nice to Have:
3+ years of experience with creating stored procedures in SQL .NET C# skills
JOB DESCRIPTION 1.Azure Platform Experience: The candidate should have hands-on experience with various Azure services including but not limited to:
Azure Data Factory, Databricks, Data Lake, and Power BI. They should be able to design, build, and maintain ETL pipelines, manage data lakes, and create insightful reports and visualizations. Experience with Azure SQL Database, Azure Synapse Analytics, Azure COSMOS DB , Azure Client, other Azure services is a plus.
SQL skill is a must to have And .NET C# skills will be a great plus.
2.Azure Data Engineer:
Design, implement, and maintain data solutions using Azure cloud services. Develop ETL processes, optimize data pipelines, and ensure data quality and security. Collaborate with teams to deliver scalable data architecture supporting analytics and business intelligence.
3.Security on Azure Platform: The candidate should have a strong understanding of security protocols within the Azure platform. This includes knowledge of identity and access management, network security, encryption methods, secure data communication, and securing serverless architectures.
4.Data Governance: The candidate should have experience in implementing data governance strategies. This includes setting up data governance frameworks, defining data ownership, ensuring data quality, and implementing data privacy and compliance measures.
Knowledge of data cataloging, data lineage, and metadata management is also important.
Hi, my name is and I am applying for the Sr. Cloud Engineer role with Client and I am open to doing an in person interview, relocating and working in a hybrid capacity , thank you.
JD: Must Have:
Ability to intrepid, modify and write scripts and SQL queries Azure Cloud Data Engineer Azure Databricks Azure Data Factory
PowerBI Report Server Python
Nice to Have:
3+ years of experience with creating stored procedures in SQL .NET C# skills
JOB DESCRIPTION 1.Azure Platform Experience: The candidate should have hands-on experience with various Azure services including but not limited to:
Azure Data Factory, Databricks, Data Lake, and Power BI. They should be able to design, build, and maintain ETL pipelines, manage data lakes, and create insightful reports and visualizations. Experience with Azure SQL Database, Azure Synapse Analytics, Azure COSMOS DB , Azure Client, other Azure services is a plus.
SQL skill is a must to have And .NET C# skills will be a great plus.
2.Azure Data Engineer:
Design, implement, and maintain data solutions using Azure cloud services. Develop ETL processes, optimize data pipelines, and ensure data quality and security. Collaborate with teams to deliver scalable data architecture supporting analytics and business intelligence.
3.Security on Azure Platform: The candidate should have a strong understanding of security protocols within the Azure platform. This includes knowledge of identity and access management, network security, encryption methods, secure data communication, and securing serverless architectures.
4.Data Governance: The candidate should have experience in implementing data governance strategies. This includes setting up data governance frameworks, defining data ownership, ensuring data quality, and implementing data privacy and compliance measures.
Knowledge of data cataloging, data lineage, and metadata management is also important.