Data Engineer Specialist

3 weeks ago

Bengaluru, India Novo Nordisk AS Full time

Department – Clinical Data Operations & Insights GBS

Are you passionate about transforming the clinical data flow and provisioning across the clinical data & technology value chain? Do you have an innovative mindset to drive change in a future-ready environment and support your colleagues and stakeholders by challenging the status quo in a friendly and open-minded way? If so, there is a job opportunity waiting for you as our new Data Engineering Specialist. At Novo Nordisk, we will challenge you to do the best work of your life. Apply Now.

The Position

As the – Data Engineering Specialist 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. Provide technical leadership and guidance to junior members of the data engineering team. Stay current with emerging technologies and industry trends related to clinical data management and data engineering. Responsible for Data Visualization and Reporting. Collaborate with data analysts and business stakeholders to design and develop data visualizations and reports to support decision-making processes. Utilize data visualization tools and techniques to present complex clinical data in a clear and understandable manner Implement data quality assurance processes to identify and resolve issues related to data accuracy, completeness, and consistency. Collaborate with teams to agree/negotiate on expectations, deliveries, timelines, etc. Lead peers, as well as collaborate with a diverse group of people and provide mentoring and guidance.

Qualifications:

Bachelor’s/ Master’s degree in software engineering, computer science, data science, mathematics, or natural sciences. Minimum 10-12 years of experience with the pharmaceutical industry or CRO or experience in working with clinical data. At least 7 years of work experience in either cloud, data engineering, or IT Infrastructure Strong technical skills in developing scalable data pipelines. Expertise in clinical data standards, either in a real-world data setting, clinical trial data standards, or similar Experience & 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, Azure and Databricks , CDISC (SDTM & ADaM), OMOP, DICOM, and similar clinical data standards, Infrastructure as code, object-oriented design, Python / Scala, Security and Authentication, API development (JSON, XML), SQL Expertise in project management, collaboration, communication and presentation skills Profound Knowledge of GxP and guidelines within drug development.

About the Department

Our 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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