Staff Data Engineer

September 6

🏡 Remote – Anywhere in Canada

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BenchSci

We empower scientists with the world’s most advanced biomedical artificial intelligence.

Antibody • Research • Machine Learning • Online Platform • Science

201 - 500

💰 Series C on 2022-01

Description

• Collaborate with multiple teams working on key customer features and our own internal development projects • Contribute to setting technical and architectural direction for our Data Engineering teams with a focus on expanding the scope of our products and our ability to make life scientists more effective • Drive the architecture of BenchSci to help us handle data more securely • Decouple work done by teams to allow for more independent work and smaller feature releases • Be involved in all aspects of software development, working to create and maintain the most reliable, secure, performant, and high throughput service for our customers by using the latest cloud technology (this can range from setting high-level technical direction down to implementation) • Translate the product vision into tangible technical solutions for execution by engineering teams • Be an inspiring mentor to other engineers • Be an advocate for us and its engineering team through several channels

Requirements

• 8+ years of professional development experience, with 2+ years at the Staff level • Expertise in data management practices, including approaches to capturing provenance, versioning, and disaster recovery • Experience working with secure data, including compliance with regulations like HIPAA and GDPR • Expertise with data processing engines such as Apache Beam and Spark • Experience working with SaaS products in a fast-paced Agile environment • The ability to lead the engineering team towards the decisions they make while minimizing friction • The ability to translate business concerns into technical implementations • Experience with mentoring technical teams • Experience with big data with integrated ML inference transformations • The ability to communicate trade-offs in approaches to security, speed to ship, and performance • Domain expertise in either machine learning, distributed systems, or cloud infrastructure • The ability to provide constructive feedback to other individual contributors while showing a sense of empathy, tact, thoughtfulness, and respect

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