Tessera Therapeutics is pioneering Gene Writing to cure disease. Our genome is a mosaic comprising genes that protect us from, predispose us to, and cause disease. Gene Editing biotechnologies heralded the era of genome-modifying medicines, but they cannot address most diseases. Gene Writing is a new biotechnology that writes therapeutic messages into the genome to cure thousands of diseases at their source.
Tessera Therapeutics was founded by Flagship Pioneering, an innovation enterprise that conceives, creates, resources, and grows first-in-category life sciences companies. Flagship Pioneering has created over 40 groundbreaking companies over the past fifteen years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Seres Therapeutics (NASDAQ:MCRB), Moderna (MRNA), Syros Pharmaceuticals (SYRS), Rubius Therapeutics (RUBY), Axcella Health (AXLA), Evelo Biosciences (EVLO), and Indigo Agriculture.
We are looking for an enthusiastic, detail-oriented, and highly motivated data engineer/data architect that can help advance our scientific mission. This person will develop and support a cloud-based infrastructure for data collection, integration and analysis for both internally and externally generated data. They will join the Quantitative Biology team and interact with computational biologists and our scientific platform teams to enable the discovery and development of novel gene therapy agents. The individual will serve as the lead designer and implementer of data solutions and expose the company to innovative technologies and systems that will help it achieve its goals.
As a key member of the scientific team, this lead data engineer/architect will:
- Design, implement and support a comprehensive, cloud-based data management infrastructure that enables the strategic scientific goals of the organization
- Rapidly create targeted solutions to critical problems
- Integrate commercial, open source and purpose-built components
- Integrate data from a variety of internal and external sources
- Build strong relationships across quantitative biology and wet bench science
- Manage any necessary license agreements, maintenance and support contracts, and any managed service relationships for the team
- Provide technical leadership and engineering for software development projects on diverse platforms
- Nucleate our automation engineering capability
- Master’s degree in Bioinformatics, Informatics, Computer Science, Data Science or other related discipline
- Minimum 3-5 years of experience in research informatics, supporting in one of the core drug discovery scientific disciplines (chemistry, biology, and clinical).
- Demonstrated experience managing cloud-based software solutions, including electronic laboratory notebooks, laboratory information management solutions, and high-performance computing.
- Demonstrated impact designing and implementing scientific information systems in a drug or target discovery setting.
- History of independently solving difficult problems, troubleshooting common research informatics problems, and proposing solutions related to informatics
- Experience working with external vendors and CROs
- History of successfully working in a cross-functional environment
- Experience working in a fast paced and rapidly growing organization
- Expertise in problem decomposition and solution delivery using modern SDLC methodologies
- Proficient with cloud development (AWS preferred)
- Results oriented: A willingness to use the right technique for the experiment, even if it’s an unfamiliar one.
- Communication: outstanding written and verbal communication skills, ability to work well with colleagues from diverse scientific backgrounds and cultures.
Preferred Qualifications, if you have these it would be a plus:
- Experience establishing DevOps foundation for software development including, source control systems, infrastructure as code standards, secure code practices, etc.
- Experience with laboratory automation systems and experimental workflow development
- Practical knowledge of high-throughput biological processes, screening or profiling
- Experience with next generation sequencing (NGS) data management
- Experience with metadata management including controlled vocabulary/ontology utilization