Software Engineer, Data Platform, QDI

QIAGEN•Redwood City, CA

15d•$120,000 - $170,000•Hybrid

About The Position

At QIAGEN, we are driven by a simple but powerful vision: making improvements in life possible. We’re dedicated to revolutionizing science and healthcare for the better. From our entrepreneurial roots to our current global presence, we've grown into a force for positive change. With thousands of employees across six continents, collaboration is our greatest strength. We’re always striving to identify talented individuals to join our exceptional teams. We have played a pivotal role in shaping modern science and healthcare, and we're just getting started. If you're someone who thrives on new challenges, values diversity and wants to make a tangible difference in people's lives, then QIAGEN is the place for you. At QIAGEN, every day is an opportunity to make a real-life impact. Join us, grow with us, and together, let's shape the future of biological discovery. QIAGEN Digital Insights is a leading provider of bioinformatics software and knowledge bases used by life scientists to gain insight from the molecular information in their biological samples. We have developed industry-leading software tools for analysis and reporting of biological data. We are passionate about our users, products, and our vision, and are seeking smart, motivated engineers and scientists who are eager to join our team in creating software that helps improve people's lives. Our mission is to make improvements in life possible. We accomplish this by designing tools used in labs all over the world to facilitate scientific discovery and progress, focused on genomics. As a Data Platform Engineer, you will play a critical role in building and scaling the systems that power the development of the world’s largest biomedical knowledge graph.

Requirements

Strong software engineering fundamentals, with experience in multiple general-purpose programming languages including Python and Java.
3+ years of industry experience in software engineering.
Deep knowledge of cloud infrastructure (preferably AWS), DevOps practices and tools, continuous integration (CI), and infrastructure as code (IaC).
Experience building and deploying data pipelines using distributed frameworks such as Spark, Hadoop, or Airflow.
A “roll up your sleeves” attitude: you take ownership of problems, relentlessly drill down to root causes, and fix issues at the source, learning new tools and technologies on the fly.
Ability to efficiently drive complex projects to completion while working collaboratively across multiple teams, including DevOps, data and ontology engineering, QA, and application software engineering.
Desire to learn the ins and outs of working with biomedical data in research and clinical applications.

Nice To Haves

Prior experience with life sciences is a plus, but not required.

Responsibilities

Design, develop, and maintain robust, scalable, high-performance data pipelines to ingest and transform vast amounts of biomedical data.
Develop tools and systems to reliably deliver high-quality content to application teams.
Accelerate and improve existing systems and workflows, taking advantage of cloud-native technologies.
Provide a delightful developer experience for our team of data engineers and content scientists, enabling them to deliver new data products faster.
Lead the adoption of strong engineering practices throughout the team, including code reviews, automated testing, and continuous integration.
Continuously improve system performance and reliability through monitoring, profiling, and postmortems / root cause analysis.