Staff Data Engineer

August 10

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Karius

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Karius is a life sciences company focused on saving lives from infectious diseases.

Life Sciences • Diagnostics • Genomics • Data Science • Bioinformatics

51 - 200

Description

• Design, develop, test, deploy, and maintain production-grade platforms and tooling that add value across the data lifecycle (ingest, transform, serve) for various use cases such as reporting, data analytics, machine learning, and bioinformatics. • Ensure centralized, standardized, and secure data access across business domains. • Combine internal (including PHI) and external data sources via ETL/ELT tooling to calculate operational and commercial KPIs for data analysis and reporting use-cases, catalyzing insight generation. • Provide support for computational teams to drive value from clinical and genomic data assets through the ML lifecycle and data science tooling Generative. • Implement generative AI solutions to increase the value and usability of Karius data assets across use-cases such as data pipelining, data discovery, knowledgebase search, and conversational analytics. • Proactively interface with cross-functional technical and non-technical stakeholders to identify unmet needs, ensure alignment with data initiatives (scope, timelines, deliverables), and communicate results and outcomes. • Coordinate with the engineering and IT domains to understand, interface with, and extend production data and software systems using engineering best practices. • Inform, implement, and follow data governance best practices and policies in conjunction with the Security and Compliance team to meet regulatory and legal requirements. • Foster a growth mindset and self-starter attitude, continually seeking opportunities for process and system improvements with a focus on quality, practicality, and delivered value.

Requirements

• B.S. degree in Computer Science, Software Engineering, Electrical Engineering, Bioengineering, or related technical fields involving algorithms or coding (e.g., Physics or Mathematics). • 10+ years of data engineering / software development experience with at least 5 years of relevant experience in building enterprise-scale data platforms. • Ability to work in a fast-paced, dynamic startup environment • Ability to balance quality and speed when building engineering systems. • Strong organizational and time management abilities. • Excellent communication and collaboration skills. • Attention to detail and commitment to delivering high-quality solutions