Data Engineer

Data Engineer is responsible for developing Life Sciences content curation and delivery system for the purpose of building life sciences databases that empower proprietary life sciences search technologies. This role encompasses developing and deploying scientific software solutions in the life sciences information space to support transformational initiatives, delivering both short and long-term results to the business.

·      Proficiency in programming languages such as Java/Scala/JavaScript/TypeScript/Python

·      Proficiency in Linux/Unix environments

·      Experience with databases technologies (relational, NoSQL, property graph, RDF/triple store)

·      Experience with data engineering tools and techniques

·      Experience building applications for public cloud environments (AWS preferred) is highly desired

·      Experience with MarkLogic/ Xquery is highly desired

·      Experience with big data technology stack (Hadoop, Spark, HDFS, EMR, Glue) is highly desired

·      Experience with AWS DevOps tools (git, Cloud Development Kit, CDK Pipeline) is desired

·      Experience building containerized applications (Docker, Kubernetes) is highly desired

·      Experience working with XML and XPath is highly desirable.

·      Experience with creating efficient XQuery algorithms is highly desirable

·      Experience with CORB2 is highly desirable

·      Experience building applications using AWS Serverless technologies such as Lambda, SQS, Fargate, DynamoDB, S3 is a plus

·      Strong communication, organizational savvy, interpersonal skills

·      Self-motivated with the ability to work with minimal supervision

·      Innovates and continuously improves; focuses on areas of highest potential

‍