

W2 Role: Azure Data Engineer with Banking/Finance Domain
β - 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.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
August 20, 2025
π - Project duration
Unknown
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ποΈ - Location type
On-site
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π - Contract type
W2 Contractor
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π - Security clearance
Unknown
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π - Location detailed
Washington, DC
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π§ - 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
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