Thermo Fisher Scientific

Data Engineer - Snowflake/AWS

Job description

Requisition Title: Data Engineer, Snowflake/AWS
Requisition ID: 200699BR

When you’re part of the team at Thermo Fisher Scientific, you’ll do important work that supports a powerful mission. With revenues of $25 billion and a track record of stability and consistent growth, we’re uniquely able to provide our teams the resources and opportunities to make significant contributions to the world of science, technology, and engineering.

Location/Division: Remote - United States Clinical Next-Generation Sequencing Division

What will you do?
Research, design, build, optimize and maintain reliable, efficient, and accessible data systems, data pipelines, and/or models.
This could be building the following:

  • Data provisioning frameworks
  • Data integration into the data warehouse, data marts, and other analytical repositories
  • Integration of analytical results into operational systems
  • Development of data lakes and other data archival stores

How will you get here?
Education:
Bachelors’ or master’s in computer science or bachelors with 8 years of experience in computer science, computer applications, information systems or engineering required. Masters’ degree with 6 years of experience

Experience:
  • 2+ year experience working with Snowflake
  • 2+ year experience working with AWS Data and Analytics technologies such as AWS Batch, Fargate, Lambda, Step Function, SQS, SNS etc.
  • 5+ year experience working with Java/JEE, Spring, Hibernate, Postgres/MySQL, Maven
  • Strong experience with building data pipelines using Python
  • Hands-on software development experience, including significant experience in full stack software development
  • Deep understanding of modern web applications design architecture, good API design patterns, security, performance, and scale
  • Experience building high-performance and scalable distributed systems
  • Experience of data migration from on premise/GCP/Azure to AWS
  • Understands the Agile mindset and iterative development process
  • Nice to have knowledge of Machine learning.

Knowledge, Skills, Abilities
  • Align closely with Enterprise partners in data science, architecture, governance, infrastructure, and security to apply standards and optimize production environments and practices.
  • Collaborate with business owners to optimize data collection, storage, and usage to maximize the value of information within supported systems.
  • Translate business needs into data solutions, designing and implementing within supported data systems and determine the division of labor across various architectural components
  • Develops, tests, and integrates new data features and functionality as defined by the product owners and business teams.
  • Experience in deploying large scale/distributed applications.

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