Senior Data Engineer

Requirements

• 3+ Knowledge of Spark, Python, or Scala
• 3+ years experience with RDBMS and T-SQL.
• 3+ years experience with NoSQL and DataLakes.
• Strong familiarity with map/reduce programming models
• Proficiency in writing production-quality code
• Deep expertise in database schema design, optimization, and scalability
• Experience with Azure or AWS cloud-based service-oriented architecture
• Solid understanding of testing pyramid (unit, integration, black box, service)
• Experience working in an Agile/Scrum environment
• Strong analytical and problem-solving skills
• Good time management and organizational skills
• Ability to work on challenging issues independently or in a team environment
• Ability to learn and adapt quickly to new technologies and environments
• Strong communication skills
• Nice-to-have's:
• Experience with Databricks or Azure ML
• Experience applying machine learning algorithms to solve complex data mining problems
• Experience with JavaScript/Typescript, HTML5, and CSS3
• Experience with .NET core and entity framework core.
• Experience with Power BI Embedded
• Understanding of cloud platforms and providers, specifically Microsoft Azure
• Knowledge of CI/CD tools in Azure DevOps
• Bachelor's Degree in Computer Science, Engineering, Mathematics or related field
• All your information will be kept confidential according to EEO guidelines.

Additional Information

You'll be part of a team that owns the AI self-service portal and the related set of microservices. You'll work with a cross-functional team of engineers to contribute to our data platform. The role also offers the opportunity to grow into either more back-end or ML/AI work depending on your interests and experience. In this role, you can expect to: - Work directly with product owners and data experts to build products that solve to solve complex client problems - Build and support a distributed platform supporting all ExParte data - Work across our product, primarily on the data pipelines - Interface directly with internal teams - Evaluate software and implementation options and document them for technical teams - Work with data analysts to collect insight on possible data collection efficiencies and identify automation potential for manual workflows - Integrate best qualitative practices in program design and development. - Be a part of a distributed team (we're in North America and Europe) - Work with Azure cloud and Databricks - Develop technical architectures and specific implementations to meet business needs.

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Company Intel

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