Senior Data Engineer

Senior Data Engineer – Cloud Computing

Location: South San Francisco

About Us

Soley Therapeutics is a biotechnology company that was created with the belief that drug discovery and development should be faster and less expensive, with a much higher probability of success. To achieve this goal, we are pioneering a novel, fully integrated approach that combines data and machine learning insights at every step of the process. We are a multi-disciplinary team that brings together experts in drug development, data engineering, and machine learning to create a cohesive platform. Our platform generates petabytes of high-dimensional imaging and multi-omics data every week, requiring scalable, high-performance data infrastructure. Our end goal is to create life-changing medical treatments by combining expertise in technology and life sciences with a comprehensive view of the entire drug discovery and development process.

Soley Therapeutics is committed to hiring a world-class team that brings together a wide variety of different skills and experiences. We are committed to inclusion across race, gender, age, religion, identity, and experience, and believe that diversity makes us stronger by bringing in new ideas and perspectives. We strive to create a workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.

About the Role

We’re looking for a Senior Data Engineer – Cloud Computing to build tools that would enable generating insights from our varied phenotypic and molecular data sources that enable our team to discover life-saving therapeutics. We are looking for mission-driven individuals that are eager to bring ideas from conception to reality.

At Soley, Data Engineers will work side-by-side with ML engineers, Data Scientists, Software Engineers and Drug Development Scientists to achieve drug discovery objectives. You will also work closely with the Lab Automation team to ensure seamless integration between experimental systems and data platforms.

The Senior Data Engineer will be responsible for building a world-class data management system. We are looking for someone who will be responsible for the delivery of complex data engineering projects to support our pre-clinical and clinical drug programs, while working closely with other senior technical leaders in science and engineering to continuously improve Soley’s data environment. Senior Data Engineers are also responsible for developing, managing, and growing our data ingestion pipelines, and leading by example with a passion for software craftsmanship and strong engineering process.

What You’ll Do

• Building data ingestion pipelines using cloud services such as AWS, OCI and Microsoft Azure, designing data storage architectures and standing up datastores on prem and the cloud.
• Creating data schema designs, setting up databases, populating databases and building tools to monitor performance and optimize data ingesting, access, and usage.
• Design and develop software tools which enable extraction, transformation, and transfer of large data sets, and managing, automating, and monitoring the data processing.
• Supporting in-house experimental assay development and combining data from multiple internal and external data sources into a universally useful and accessible data platform.
• Collaborate with scientific and engineering leaders to develop engineering requirements, development roadmaps, project plans and work priorities.
• Be able to work independently, collaborate as needed with team members, take ownership of assigned projects and set and keep a high-quality engineering bar for all projects.
• Develop tools to monitor the status and health of hardware systems and devices and collaborate with IT to investigate and resolve IT issues.
• Collaborate closely with the Lab Automation team to integrate experimental workflows, instrumentation, and real-time data capture into scalable pipelines.
• Design and maintain production-grade data pipelines supporting both lab automation systems and machine learning workflows, ensuring reliability, scalability, and observability.
• Develop and manage infrastructure to support extremely large-scale datasets (petabyte-scale imaging and multi-omics data) with efficient storage, retrieval, and processing.

What You Bring

• Education: Bachelors and/or Graduate Degree in Computer Science, or a Big Data related field.
• Cloud Computing: Deep knowledge of cloud computing platforms, such as AWS, OCI and Azure, and experience setting up and managing cloud computing and storage resourcesl, and experience setting up and managing cloud computing and storage resources, including containerized environments (e.g., Docker, Kubernetes, dev pods).
• Data Engineering: Experience architecting data warehouses, metadata management, including data catalogs, controlled vocabularies/ontologies, and provenance; knowledge of data pipelines and architectures to enable efficient and effective large-scale data processing workflows.
• Experience working with large datasets, especially imaging or multi-omics data, and optimizing pipelines for stability, throughput and cost.
• Biotech/BioPharma experience: 5+ years’ experience working with real world medical or genomic data in industry or deep technical academic setting.
• Programming: Extensive experience with data engineering programming in Python, Java, C++, or other relevant language, software development lifecycle, and code management. Working knowledge of batch and stream processing technologies such as Apache Spark and Apache Flink, how they work under the covers, and ability to trade-off pros/cons of different tools/approaches.
• Project Management: Experience with workflow management tools and platforms.
• Communication: Demonstrated ability to effectively communicate with and influence business and technical teams.
• Attitude: Eagerness to learn new skills, wear many hats, and collaborate closely with a growing team of people.

You May Also Bring

• Experience designing, developing, launching, and maintaining a company-wide data lake and data warehouse supporting diverse types of data and data science workflows.
• A background in drug development or another healthcare or biotechnology field.