Data Engineering Leader for Knowledge Graph
6 days ago
About the Role: In this role, you will work closely with cross-functional teams to scale data pipelines, manage sources of semi-structured and unstructured biological data, and collaborate on complex data mining and extraction challenges. You will also design testable, scalable solutions using the latest frameworks and tools.
Key Responsibilities:
- Scale data pipelines to allow research data to quickly and reliably go from research to platform
- Manage sources containing semi-structured and unstructured biological data contributing to the evolution of our Knowledge Graph
- Integrate public life science data into our biological ontology in the Knowledge Graph
- Collaborate with ML, Data Engineers, and Science teams to solve complex data mining and extraction challenges
- Design testable, scalable solutions to complex problems using the latest frameworks and tools
About You: To be successful in this role, you should have 5+ years of experience working as a professional data engineer in industry, expertise in Python coding and type system, and expertise in writing SQL (GQL, PostgreSQL, and BigQuery are a plus). Experience with building batch and streaming ETL pipelines, cloud development (we use GCP and Terraform), and large-scale data manipulation/transformations is also required. A can-do proactive and assertive attitude, outstanding verbal and written communication skills, and experience executing as part of high-performance engineering teams are essential. An estimated salary for this position is $170,000 - $210,000 per year based on location, depending on your level of experience and qualifications.
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