PlatformQ Health is a leading digital medical education provider, producing live and enduring online Continuing Medical Education (CME) activities in a convenient and engaging interactive format. This pioneering approach to online education makes it time efficient and cost-effective for healthcare professionals to stay current with the latest clinical developments and treatment options. PlatformQ Health currently designs, develops and provides education in over 13 therapeutic areas, including oncology, neurology, rare diseases, cardiology, infectious disease and immunology. The Company has strategic partnerships with leading medical societies, associations, advocacy groups and foundations. Examples include ASGCT, NORD, KDIGO and AAFA.
The Senior Data Engineer will be responsible for designing and developing data pipelines and services using Python and AWS. The Senior Data Engineer will join a team of data engineers and will be responsible for designing, monitoring, and maintaining data pipelines and integrations. They will work to ensure data accuracy and integrity within the system and will be responsible for monitoring the stack for proactive resolutions. The Senior Data Engineer will also be responsible for providing technical guidance, documentation, and mentorship to other members of the engineering team.
The ideal candidate should have a strong background in data engineering, data warehousing, ETL/ELT pipelines, and architecting creative data solutions. The candidate should be a self-starter and also have a desire to learn about ML ops in order to support future-looking machine learning initiatives.
- Design, develop and maintain ETL/ELT pipelines using AWS cloud
- Mentorship of the data engineering team in the form of code reviews, guidance, and upskilling
- Collaborate with software engineers, product managers, and business stakeholders to understand requirements and data needs
- Develop and maintain PlatformQ’s data warehouse and reporting architectures
- Proactively monitor, troubleshoot, and optimize data pipelines
- Design and develop data applications and services that enable self-service reporting and analysis
- Ensure data integrity and accuracy
- Stay current with emerging technologies and industry trends related to data engineering
- Basic data privacy and security principles
- 5+ years of experience in data engineering.
- Demonstrated team mentorship or leadership experience
- Extensive experience in the design, development, and maintenance of data ETL pipelines.
- Extensive knowledge of coding in Python with a focus on data processing.
- Experience implementing the AWS technology stack (S3, Redshift, Lambda).
- Experience with data and entity relationship modeling to support data warehouses and analytics solutions including downstream reporting solutions.
- Experience with relational and non-relational databases (SQL/NOSQL).
- Comfortable working with unstructured and semi-structured data as well as working with APIs
- Experience working in a professional software environment using source control (git), an issue tracker (JIRA, Confluence, etc.), code reviews, and agile development process.
Nice to Have:
- Experience with machine learning workflows and data requirements for use with ML frameworks
- Experience with containerization using Docker
- Experience with open-source tools like Apache Airflow and Superset
- Experience with AWS services like Step Functions, Glue, and Sagemaker
- Experience with AWS IaC services like SAM or CloudFormation
Please send your resume to email@example.com