Principal Engineer, Software Development Engineewring(Apps)

We are seeking a highly skilled and motivated Principal Engineer with expertise in .NET Core and Python for data science to join our dynamic team. The ideal candidate will possess a strong foundation in software development and data analysis, capable of leveraging these skills to deliver innovative solutions and insights. As a senior developer, you will be instrumental in developing and optimizing our data-driven applications and systems.

Key Responsibilities:

• Develop and Maintain Applications: Design, develop, and maintain robust applications using .NET Core and Python.
• Data Analysis and Modeling: Perform data analysis, create predictive models, and develop data-driven solutions to support business objectives.
• Integration: Integrate data from various back-end services and databases, ensuring seamless data flow across systems.
• Collaboration: Work closely with cross-functional teams, including data engineers, data scientists, and business stakeholders, to gather requirements and deliver solutions.
• Performance Optimization: Optimize applications for maximum speed and scalability.
• Code Quality: Write clean, scalable, and maintainable code, ensuring adherence to best practices and industry standards.
• Research and Development: Stay up-to-date with the latest industry trends and technologies in .NET Core, Python, and data science, and apply this knowledge to improve existing processes and systems.

Tech Stack:

• .NET Core:
  • ASP.NET Core: For building web applications and APIs. (.NET Core MVC, Ado.Net, C#, WCF, Web Services, Windows, )Services, SSIS, MSMQ, Web Sockets
  • Entity Framework Core: For ORM (Object-Relational Mapping) and data access or Dapper.
  • SignalR: For real-time web functionalities.
  • IdentityServer: For authentication and authorization.
• Python:
  • Open Telemetry Stack
  • Pandas: For data manipulation and analysis.
  • NumPy: For numerical computations.
  • Scikit-Learn: For machine learning algorithms.
  • TensorFlow/Keras: For deep learning and neural networks.
  • Matplotlib/Seaborn: For data visualization.
  • Jupyter Notebooks: For interactive data exploration and visualization.
• Databases:
  • SQL Databases: Such as SQL Server, PostgreSQL, or MySQL for relational data management.
  • NoSQL Databases: Such as MongoDB or Cassandra for non-relational data management.
  • Data Warehouses: Such as Azure Synapse Analytics, AWS Redshift, or Google BigQuery.
• Cloud Platforms (Any one):
  • Microsoft Azure: For cloud services, including Azure App Services, Azure Functions, Azure SQL Database, and Azure Machine Learning.
  • AWS: For cloud services, including AWS Lambda, Amazon RDS, and Amazon SageMaker.
  • Google Cloud Platform (GCP): For cloud services, including Google App Engine, Anthos, Cloud Functions, and BigQuery.
• DevOps:
  • CI/CD Tools: Such as Azure DevOps or Jenkins or GitHub Actions or GitLab CI.
  • Containerization: Using Docker to create and manage containers.
  • Orchestration: Using Kubernetes for container orchestration.
  • Version Control: Using Git for source code management.
• Front-End Technologies (Preferred):
  • JavaScript Frameworks: Such as React, Angular, or Vue.js.
  • HTML/CSS: For web development.
• APIs:
  • RESTful APIs: For standard API development.
  • GraphQL: For flexible API queries.

• Education: Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related field.
• Experience: Minimum of 7-10 years of experience in software development and data science, with a strong emphasis on .NET Core and Python.
• Technical Skills:
  • Proficiency in .NET Core and Python.
  • Strong experience with data science libraries and frameworks (e.g., GCP, BigData, ).
  • Experience with SQL and NoSQL databases.
  • Familiarity with RESTful APIs and microservices architecture.
  • Knowledge of front-end technologies (e.g., HTML, CSS, JavaScript) is a plus.
• Analytical Skills: Strong analytical and problem-solving skills, with the ability to analyze complex data sets and derive actionable insights.
• Communication Skills: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Team Player: Proven ability to work effectively in a collaborative team environment.
• Adaptability: Ability to adapt to changing business requirements and work in a fast-paced environment.

Preferred Qualifications:

• Certifications: Relevant certifications in .NET Core, Python, or Data Science.
• Cloud Experience: Experience with cloud platforms such as Azure, AWS, or Google Cloud.
• Machine Learning: Hands-on experience with machine learning algorithms and frameworks.
• DevOps: Familiarity with DevOps practices and tools (e.g., Docker, Kubernetes, CI/CD pipelines).

All your information will be kept confidential according to EEO guidelines.