Head of Data Engineering Clinical

3 weeks ago

Anthony, United States Recruit Year Full time
About the Role

We are seeking a highly skilled Head of Data Engineering Clinical to lead the development and application of our data engineering platform. This is a visionary and hands-on role that requires a strong player-coach mentality to balance the needs of leading two groups: data platform (data engineering) and search/enrichment (ML engineering).

The ideal candidate will have a proven record of accomplishment leading successful large-scale clinical data initiatives within a product-focused environment. They will have a strong background in applied data engineering and data pipelines with hands-on experience developing and deploying production-ready models.

The successful candidate will work closely with stakeholders to continuously innovate our platform, ensuring it stays ahead of the curve in supporting the mission of the organization. They will be tasked with scaling the data ingestion and comprehension of one of the largest and densest sets of rich unstructured clinical data.

Key Responsibilities
  • Lead the continued development and enhancement of our clinical data ingestion and comprehension pipeline.
  • Drive the utilization of core principles in development, including observability, scalability, and end-to-end control.
  • Support the utilization of advanced AI/ML research through the exposure of raw, canonicalized, and comprehended data in analytics platforms.
  • Establish and maintain key performance metrics to track the effectiveness of data engineering initiatives.
  • Foster collaboration with internal and external stakeholders to gather feedback and drive continuous improvement.
Requirements
  • Strong player-coach mentality with an ability to balance the hands-on needs of leading two groups: data platform (data engineering) and search/enrichment (ML engineering).
  • Proven record of accomplishment leading successful large-scale clinical data initiatives within a product-focused environment.
  • Strong background in applied data engineering and data pipelines with hands-on experience developing and deploying production-ready models.
  • Understanding of Software Development Life Cycle and data product development.
  • Experience working with healthcare data, especially HL7 and FHIR.
  • Deep understanding of streaming data ingestion and ETL processes.
  • Conceptual understanding of ML techniques, particularly NLP (e.g., NER, BERT).
  • Conceptual understanding of AI techniques, like large language models (LLMs), self-learning models (SLMs), and other state-of-the-art approaches.
  • Experience with database technologies, especially Elasticsearch, PostgreSQL, Amazon Aurora, and DynamoDB.
  • Demonstrated passion for staying up to date with the latest data engineering and pipeline trends along with a record of accomplishment of driving innovation.

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