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Senior Principal Data Engineer

4.00 to 9.00 Years   Bangalore   16 Jun, 2023
Merck Ltd
Job LocationBangalore
EducationNot Mentioned
SalaryNot Disclosed
IndustryPharma / Biotech
Functional AreaGeneral / Other Software
EmploymentTypeFull-time

Job Description

    Company Healthcare R&D Data Sciences seeks biological data engineering support for data analysis activities, to build our FAIR data environment, and to streamline our data handling. Omics Data Engineering will play a pioneering role in establishing this new group and a leading role in building tools and setting standards for biological data. Our Data Engineers will work in Companys X-Omics Platform, which won the 2022 BioIT Innovative Practices Award. Omics Data Engineers will work on clinical and pre-clinical datasets but their focus is biological data types (e.g., DNA sequencing, proteomics, gene expression, collectively omics data ). While the group will be responsible for routine data engineering tasks, its success will be measured by the extent to which activities can be automated, problems anticipated, and attention focused on our data strategy. Data engineers will collaborate daily with scientists at Companys other R&D hubs and across departments. Ideal candidates will have a background with biological data, perhaps through bioinformatics or data management experience. Specific responsibilities for data engineers include
        • building tools to automate data transfers and QC
        • working with other Data Sciences functions on an R&D-wide data catalog
        • developing and implementing standards for data formats, processing, and documentation
        • training internal users on data standards, data formats, and data assets
        • running pipelines for raw data analysis
        • arranging and managing data transfers with CROs and data providers
    Core qualifications for Omics Data Engineers
        • experience with data engineering, data management, and cleaning in biology or healthcare
        • attention to detail and ability to lead work with multiple parties (analyst, data type subject matter expert, external lab, etc.) to accomplish data transfers efficiently
        • experience with R and Python programming, as well as other tools/technologies such as RShiny and SQL
        • experience with Linux command line, shell scripting, and AWS S3
        • experience with controlled vocabularies and ontologies
    Preferred qualifications include:
        • RNASeq and DNASeq data processing
        • Familiarity with ADaM or SDTM data standards
    ,

Keyskills :
sqljavadata warehousinginformaticapythondna sequencingdata standardsshell scriptingdata managementgene expressiondata engineering

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