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# C#/.NET and Data Engineer

- **Company:** S&K GLOBAL SOLUTIONS LLC
- **Location:** Bellevue, WA, United States
- **Contract:** Permanent contract
- **Skills:** ASP.NET, .NET Framework, Microsoft Azure, Big Data, C Sharp (Programming Language), Cloud Engineering, Code Review, Information Engineering, Data Governance, Software Debugging, Distributed Computing Environment, Object-Oriented Software Development, Performance Tuning, Software Engineering, PL-SQL, Software Organization, Cloud Platform System, Data Ingestion, Apache Spark, Backend, Data Management, Restful APIs, Data Pipelines, Databricks, Microservices
- **Published:** August 15, 2026
- **Apply:** https://www.dice.com/job-detail/d3df0fe8-38d2-47c2-99ce-3920a5387d67

## About the Role

Data Engineering; PL/SQL; ADF; Digital : Azure Databricks; ASP.NET 2.0; C# 4.0

Roles & Responsibilities

Software Engineering (C#/.NET)

Strong experience designing, developing, and maintaining production-grade applications and services using C# and modern .NET technologies.

Proficient in building scalable, reliable, and high-performance backend systems, REST APIs, and microservices.

Experienced in software development best practices including object-oriented design, code reviews, testing, debugging, and CI/CD automation.

Skilled in troubleshooting complex production issues and delivering robust solutions in enterprise environments.

Familiar with cloud-native application development and integration with Azure services.

Data Engineering

Experience working with large-scale datasets, data platforms, and end-to-end data engineering solutions.

Proficient in building, optimizing, and supporting data pipelines for data ingestion, transformation, and analytics workloads.

Hands-on experience with distributed data processing technologies and modern analytics ecosystems.

Familiarity with Databricks, Apache Spark, and cloud-based data platforms for handling high-volume and high-velocity data.

Understanding of data governance, data quality, performance optimization, and scalable data architecture principles.



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