Data Engineering Lead in Mississauga, ON
- Title: Data Engineering Lead
- Code: RCI-21694
- RequirementID: 106755
- Location: Mississauga, ON L5N 5M8
- Posted Date: 03/13/2023
- Duration: 12 Months
- Name:Anthony Blomer
- Email: email@example.com
- Phone: 908-704-8843 ✖
We need a Data Engineering Lead to help us create a next generation data engine that is scalable and rigorously ingests and transforms data generated from this initiative so they are ready for machine-driven analysis. The Data Engineering Lead will act as an architect and engineering manager tasked to oversee the construction and operation of this data engine.
This data engine will be used to help assemble an exabyte scale connected and computable data universe composed of high value internally and externally generated data and results that we can build our data science efforts on top of. Your efforts will therefore directly enable computational discovery of disease targets and from these potentially lifesaving therapies.
A person hired in this position will
- Manage a team that will architect and deliver a next generation data engine that enables scalable, flexible, and rigorous data transformations using modern data management practices.
- Help architect and deliver data infrastructure that will enable machines to crawl and compute on and across all our data.
- Work with a cross functional team of scientists and engineers to design and deliver these solutions.
- Exert influence across the informatics organization via presentations and collaborations.
Successful candidates will meet many of the following requirements:
- You have a BS in a computational discipline with 12 years of work experience or a Masters with 7 years of experience.
- 7+ years’ experience architecting and developing scalable pipelines, frameworks and platforms to power data science efforts in distributed cloud environments, 5 of which are on AWS.
- Multiple years of experience leading a distributed team of engineers to deliver solutions.
- Exceptional communication skills.
Nice to haves:
- Practical understanding of the data management practices required to power rigorous data science and enable advanced analytics like AI & ML.
- Hands-on experience working with the following technologies, frameworks, and languages: Java, Scala, Python, Spark, Airflow, RabbitMQ, Spring (nice to have).
- Experience leading projects focused on omics data (nice to have)
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