Practice Architect- Lifesciences @ CitiusTech

• Asa Practice Architect - Life Sciences , you will be responsible for designingand implementing data engineering solutions for life science organizations

• They collaborate with clients to understand their business needs and createcustom solutions that meet their requirements
• They also provide guidance andexpertise to internal teams to ensure that data engineering projects arecompleted on time and within budget
• Lead the design and implementation of data engineering solutions for life science organizations.
• Collaborate with clients to understand their business needs and create custom solutions that meet their requirements .
• Provide guidance and expertise to internal teams to ensure that data engineering projects are completed on time and within budget.
• Develop and maintain data engineering standards and best practices .
• Identify and recommend new technologies and tools to improve the efficiency and effectiveness of data engineering projects.
• Develop and maintain relationships with key stakeholders in the life science industry .
• Provide thought leadership and subject matter expertise in data engineering for life science organizations.

Education

• Bachelor s or Master s degree in Computer Science, Engineering, or a related field.
• Technical certification in multiple technologies is desirable.

MandatorySkills

• Strong knowledge of data engineering tools and technologies, including ETL, data warehousing, data integration, data processing pipelines.
• Experience working with life science data, at least one of clinical trial data, genomics data, or electronic health records.
• Experience with cloud-based data engineering solutions, such as AWS, Azure, or Google Cloud.
• Minimum of 10 years of experience in data engineering, with a focus on life science organizations.
• Knowledge of life science industry regulations and compliance requirements, such as HIPAA and GDPR.
• Strong communication and collaboration skills, with the ability to work effectively with clients and internal teams.
• Ability to lead and manage data engineering projects from start to finish.
• Strong analytical and problem-solving skills, with a focus on data quality and accuracy.

DesiredSkills

• Experience with machine learning and artificial intelligence tools and techniques for data analysis.
• Knowledge of data visualization tools and techniques for presenting data insights to clients and stakeholders.
• Experience with Agile software development methodologies and project management tools such as Jira or Trello.
• Ability to mentor and train junior data engineers and developers in the life science domain.
• Experience with data security and privacy best practices for life science organizations.