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Hi Proferssionls, we have a position for .NET Engineer at Chicago IL (Locals only) on W2 Title:.NET Engineer on W2 Location: Chicago IL(Locals only) Duration : Long term contract Candidate must have ...
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Chicago, IL · On-site
$118K - $141K/yr
.NET Engineer Location: Chicago, IL Local Candidates Only We are seeking a skilled .NET Engineer with strong data engineering experience to design, develop, and maintain data pipelines, backend ...
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Hi Proferssionls,
we have a position for .NET Engineer at Chicago IL (Locals only) on W2
Title:.NET Engineer on W2
Location: Chicago IL(Locals only)
Duration : Long term contract
Candidate must have skills .NET/C#, data engineering skills (Snowflake, Python, Airflow)
Key Responsibilities
Data Pipeline Development: Build, orchestrate, and maintain automated ETL/ELT pipelines using C#/.NET Core and cloud tooling (e.g., Azure Data Factory).
Backend Data Services: Develop high-performance custom data ingestion tools, integration components, and RESTful APIs using the .NET framework.
Database & Warehouse Optimization: Design, implement, and fine-tune complex relational database schemas (SQL Server, PostgreSQL) and data warehouses.
Legacy Modernization: Refactor and modernize legacy data frameworks or storage layers, upgrading older .NET infrastructure to modern cloud-native standards.
Data Integrity & Cleansing: Implement structured validation checks, automated testing frameworks, and error-handling routines inside data processing flows.
DevOps & Orchestration: Establish automated CI/CD deployment pipelines for data infrastructure using tools like Azure DevOps, GitHub Actions, and Git.
Collaboration: Partner with full-stack developers, data analysts, and product teams to expose analytical datasets and fulfill enterprise reporting needs.
Required Qualifications
Core Programming: Expert-level knowledge of C#, .NET Core/.NET 10+, and SQL.
Cloud Architecture: Hands-on experience working inside a major cloud ecosystem, preferably Microsoft Azure (Azure Data Lake, Azure Synapse, Cosmos DB, Azure Functions).
Data Infrastructure: Solid understanding of data modeling concepts (Snowflake, Python, Airflow, Star schemas, dimensional modeling) and indexing strategies.
Tools & Tooling: Proficient with Git, version control, and containerization platforms like Docker.