Lead Data Engineer

2 weeks ago


Bengaluru, India Novo Nordisk AS Full time
Department – Clinical Data Operations & InsightsLocation: BangaloreAre you passionate about transforming the clinical data flow and provisioning across the clinical data & technology value chain? Do you have experience in ETL processes and data engineering? We are looking for a Lead Data Engineer to join our Clinical Data Operations & Insights group at Novo Nordisk. If you are ready for a challenging and rewarding career, read on and apply today for a life-changing opportunity.The PositionAs the Lead Data Engineer at Novo Nordisk, you will be responsible for driving the development and maintenance of various clinical data sources, data review models, etc. Responsible for developing and maintaining robust scalable ETL (extraction, transformation, load) processes for complex clinical data sources, including electronic health records (EHR), clinical trial databases, and other relevant sources. Support the development and implementation of next-generation clinical data infrastructure. Design and implement logical clinical data flow to ensure efficient data capture, transformation, and integration.You will be entrusted with the following responsibilities:Responsible for creating value throughout the value chain by enabling real-time analytics of our clinical data, including data from clinical studies, real-world data, multi-omics, images, streaming data, and more Data Quality Assurance and Database Management.Develop and maintain a comprehensive understanding of clinical data sources, including electronic health records (EHR), clinical trial databases, and other relevant sources.Responsible for designing, developing, and maintaining ETL processes to extract, transform, and load clinical trial data from various sources into data warehouses or other target systems.Ensure compliance with regulatory requirements and industry standards for clinical data management, such as HIPAA and GDPR. Establish and enforce data governance policies and procedures to maintain data integrity and confidentialityLead conceptualization and development of data visualizations and reports to support decision-making processes. Utilize data visualization tools and techniques to present complex clinical data clearly and understandably.Qualifications:Bachelor’s/ Master’s degree in software engineering, computer science, data science, mathematics, or natural sciences.Minimum 8-10 years of experience with the pharmaceutical industry or CRO or experience working with clinical data.Relevant years of work experience in either cloud, data engineering, or IT Infrastructure.Strong technical skills in developing scalable data pipelinesExpertise in clinical data standards, either in a real-world data setting, clinical trial data standards, or similarExperience in and/or knowledge of some or most of the below-listed technologies/ standards: Data lineage and ontologies, ETL tools, and techniques, such as Informatica, Talend, or Apache NiFi,Experience in Azure and Databricks

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CDISC (SDTM & ADaM), OMOP, DICOM, and similar clinical data standards, Infrastructure as code, Object Oriented Design, Python / Scala, Databricks Delta Lake, Security and Authentication API development (JSON, XML), SQLExperience in project management, collaboration, communication, and presentation skills.Profound Knowledge of GxP and guidelines within drug development.About the DepartmentOur Clinical Data Operations & Insights group is about 400 professionals spanning across India, Denmark, and North America. Data Management sits in Development where we manage clinical drug development worldwide, ensuring that the process lives up to uniform global standards, regulations, and business ethics while delivering viable products that make a difference to patients and ultimately benefit society. Our newly formed Data Review and Cleaning group sits within the Data Management & Centralised Data Review Department led from our Bengaluru site. The Data Review and Cleaning group has been set up to centralize and modernize the data review and cleaning processes, implement new methodologies, and develop innovative toolkits supporting the transformation.

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