Senior Data Engineer (Remote)

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.

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