Job Description
MMS is an innovative, data focused CRO that supports the pharmaceutical, biotech, and medical device industries with a proven, scientific approach to complex trial data and regulatory submission challenges. Strong industry experience, technology-enabled services, and a data-driven approach to drug development make MMS a valuable CRO partner, creating compelling submissions that meet rigorous regulatory standards. With a global footprint across four continents, MMS maintains a 97 percent customer satisfaction rating, and the company has been recognized as a leading CRO in Global Health & Pharma’s international awards programs for the last three consecutive years. For more information, visit www.mmsholdings.com or follow MMS on LinkedIn.
Job Description:
- Maintains a strong understanding of regulations and guidance as they pertain to data curation deliverables.
- Strong understanding of new methods, tools and solutions to meet the Data Engineering needs of internal and external stakeholders and teams.
- Mentors others and advises on MMS, industry trends and technologies to give the technical and non-technical stakeholders a better understanding of data science methodologies and results.
- Maintains a strong understanding of Data Science department methodologies and standard practices.
- Proficient in conducting peer reviews for others and validation of project deliverables within the team.
- Proficient in developing and delivering training for internal and external stakeholders regarding Data Engineering processes and deliverables.
- Strong understanding of CROs and/or Health Systems and the drug development process.
- Proficient in developing requirements and specifications from analysis of business needs.
- Proficient in preparing, correcting, modifying and analyzing data sets using complex analytic techniques.
- Create reusable, highly parameterized pipelines using Microsoft Azure, driven by project-based configuration files to orchestrate landing data in the data lake as well as staging to SQL databases for analysis.
- Apply data modeling and architecture best practices to stage and transform data to a common data model. Incorporate data warehouse concepts to support dashboard reporting via star schemas and support auditing via data lineage concepts.
- Ability to write T-SQL stored procedures, master window functions, common table expression, and derived tables, utilize dynamic T-SQL, ability to optimize and tune queries and processes.
- Thinks like a software developer. Always looking to refactor code, utilize patterns, think abstractly, and work in ways to encapsulate logic to reduce coding side effects.
Requirements:
- College graduate in Data Engineering discipline or related field, or related experience.
- Minimum of 7 years’ experience in Data Engineering or similar field required or an equivalent combination of education and experience.
- Create reusable, highly parameterized Azure data factory pipelines, driven by project-based configuration files to orchestrate landing data in the data lake as well as staging to Microsoft SQL databases for analysis.
- Apply data modeling and architecture best practices to stage and transform data to a common data model. Incorporate data warehouse concepts to support dashboard reporting via star schemas and support auditing via data lineage concepts.
- Ability to write T-SQL stored procedures, master window functions, common table expression, and derived tables, utilize dynamic T-SQL, ability to optimize and tune queries and processes.
- Thinks like a software developer. Always looking to refactor code, utilize patterns, think abstractly, and work in ways to encapsulate logic to reduce coding side effects.
- Expert knowledge of Data Engineering concepts.
- Reputation as emerging leader in field with sustained performance and accomplishment.
- Hands-on experience with clinical trial and pharmaceutical development preferred.
- Good communication skills and willingness to work with others to clearly understand needs and solve problems.
- Excellent problem-solving skills.
- Good organizational and communication skills.
- Familiarity with data privacy and anonymization regulations preferred.
- Familiarity with current ISO 9001 and ISO 27001 standards preferred.
- Familiarity with 21 CFR Part 11, FDA, and GCP requirements.
- Familiarity with industry standard data models (CDISC, FHIR, OMOP) preferred.
- Basic understanding of CROs and scientific & clinical data/terminology, & the drug development process
- Proficiency with MS Office applications.
Powered by JazzHR
XVfUMwbOJN