Sr. Data Architect (Pharma/Life Sciences)
Location : Manhattan, NY – On-site
Salary : 250-350K
Must have the following skills:
~Strong Education with a High GPA with either a BS, Masters, or PhD.
~Must have 5+ years of experience with a proven background working with petabytes of data, hundreds of millions of rows.
~Must have some proven Life Sciences background.
~Must have a strong architecture background.
~Must have a strong Python and or C/C++ coding background. Must be able to show high-level coding of thousands of lines of code.
~Loves to be hands-on and technical
~Must show a link to repositories to show samples of your work.
Please only share your resume if you meet ALL of the qualifications above.
We are seeking a highly qualified Senior Data Architect with a strong background in Life Sciences to join our dynamic team. The ideal candidate will have a robust education, extensive experience handling massive datasets, and a proven track record of architectural design and implementation. If you’re passionate about leveraging data to drive advancements in the Life Sciences industry and possess exceptional technical skills, we want to hear from you.
Key Responsibilities:
Design, develop, and maintain robust data architectures capable of handling petabytes of data and hundreds of millions of rows, specifically tailored for Life Sciences applications.
Collaborate with cross-functional teams to understand data requirements and translate them into scalable architectural designs.
Implement best practices for data management, ensuring data integrity, security, and performance.
Lead the development and implementation of data pipelines, ETL processes, and data integration strategies.
Conduct performance tuning and optimization of database systems to meet organizational objectives.
Mentor junior team members, providing guidance on architectural principles and best coding practices.
Requirements:
Strong educational background with a BS, Masters, or PhD in Computer Science, Data Science, Bioinformatics, or related field. A high GPA is preferred.
5+ years of professional experience working with petabytes of data and handling hundreds of millions of rows, preferably within the Life Sciences domain.
Proven track record of designing and implementing complex data architectures, demonstrating expertise in scalability, reliability, and performance optimization.
Deep understanding of Life Sciences concepts and workflows, with experience in areas such as genomics, proteomics, drug discovery, or clinical research.
Proficiency in Python and/or C/C++ programming languages, with the ability to showcase high-level coding skills through repositories or samples of work.
Hands-on mentality with a passion for technical challenges and a willingness to dive into complex problems.
Excellent communication skills with the ability to collaborate effectively with cross-functional teams and articulate complex technical concepts to non-technical stakeholders.
Preferred Qualifications:
Experience with cloud-based technologies such as AWS, Azure, or Google Cloud Platform.
Familiarity with big data frameworks and technologies such as Hadoop, Spark, or Kafka.
Knowledge of containerization technologies like Docker and orchestration tools such as Kubernetes.
Previous experience in building and maintaining scalable data infrastructure in a regulated environment (e.g., FDA compliance).
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