W2 Role: Azure Data Engineer with Banking/Finance Domain

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Azure Data Engineer with Banking/Finance domain experience, located onsite in Washington DC. The contract is W2, requiring expertise in ADF, PySpark, Azure SQL Database, and data warehousing concepts.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
August 20, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
On-site
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πŸ“„ - Contract type
W2 Contractor
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Washington, DC
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🧠 - Skills detailed
#PySpark #Spark (Apache Spark) #NoSQL #Azure SQL Database #Data Engineering #Azure #Cloud #Data Integration #Azure SQL #Data Lake #Big Data #SQL (Structured Query Language) #Data Warehouse #Data Modeling #RDBMS (Relational Database Management System) #SQL Server #Microsoft Azure #Azure Data Factory #Synapse #"ETL (Extract #Transform #Load)" #ADF (Azure Data Factory) #Data Catalog #Oracle #Azure SQL Data Warehouse #Storage #MS SQL (Microsoft SQL Server)
Role description
Job Title : Azure Data Engineer with Banking/Finance Domain Exp. Preferred Location : Washington DC (Onsite from day1) Duration : Contract - W2 Role Banking/Finance domain experience preferred. Looking for candidate who can work on W2 only. Job Description: Key Skills: ADF, Pyspark, ADB and good knowledge in Data warehousing skills β€’ In-dept knowledge and hands-on experience in Microsoft Azure data stack i.e. Azure Data Factory, Azure Synapse, Azure SQL Database, etc. β€’ Experience of big data approach, architectural concepts, data sourcing/ ingestion/ curation and storage mechanisms. β€’ Experience with real-time / near-real-time data warehousing concepts and design approaches. β€’ Good understanding of OLTP and OLAP concepts and Strong knowledge on design concepts of Database and Data ware housing systems. β€’ Must have strong development & design skills in SQL and PL/SQL areas in RDBMS environments e.g. MS SQL Server and Oracle 11g/18c/19c. β€’ In-depth knowledge of NoSQL database usage within enterprise context and design/ modeling approach β€’ Building and migrating the complex ETL pipelines from on premise system to cloud database such as Azure SQL Data warehouse, Spark to make the system grow elastically β€’ Provide a high level of ETL technical services and support; is considered an expert in multiple ETL technologies; maps data source to destination β€’ Building and migrating the complex ETL pipelines from on premise system to cloud database such as Azure SQL Data warehouse, Spark β€’ Provide a high level of ETL technical services and support; is considered an expert in multiple ETL technologies; maps data source to destination β€’ Experience building Azure data lake ETL pipelines component such as Azure Data lake Analytics, Azure SQL database and SQL Datawarehouse. β€’ Expertise with data modeling on Azure SQL database and SQL Datawarehouse β€’ Expertise with building Azure data catalogue β€’ Data Integration : Building Pipeline and workflows (ETL) with Azure data factory