Staff Observability Engineer
GroqFull Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Candidates should possess 8+ years of experience in designing and developing distributed systems for collecting and processing large datasets. Proficiency in Node.js, Typescript, or Python, along with Apache Spark, Databricks, Spark Structured Streaming, and the Delta file format is required. Experience with container technologies like Docker, cloud infrastructure providers (AWS, Azure, or GCP), databases and SQL, Linux, and cloud-based performance tuning is also necessary. Familiarity with Superset or other analytics/charting tools, strong application debugging skills, and good communication skills, including technical writing, are essential. A Bachelor's or Master's degree in Computer Science or an equivalent major is needed, with experience in Life Sciences or scientific data being a significant advantage.
The Senior Software Engineer will join the data administration and monitoring team to build highly scaled observability solutions for collecting and analyzing telemetry from integrations and platform services. This role involves self-starting and making progress in ambiguous situations, designing and developing efficient solutions for extracting observability data, and ensuring the resiliency, scale, and high availability of observability tools and monitored systems. The engineer will deliver high-quality products using agile methodologies, partner with product management to translate visions into reality, and collaborate effectively with a geographically dispersed team across different time zones. They will also be expected to represent their positions clearly, remain resilient, and be open to constructive feedback.
Cloud platform for scientific data management
TetraScience offers a cloud-based platform called the Scientific Data Cloud, which helps biopharmaceutical companies manage and harmonize their scientific data for research and development, quality assurance, and manufacturing. The platform connects various lab instruments and software, streamlining data management and significantly reducing task completion time. TetraScience's vendor-neutral and open design allows it to work with any lab equipment, making it a flexible solution in the life sciences sector. The company's goal is to enhance scientific outcomes by preparing data for artificial intelligence and machine learning applications.