Manager - Real World Data Engineering

Key Responsibilities

• Facilitating the integration of diverse data types and sources to provide a comprehensive view of patient health and treatment outcomes.

• Provide coaching and peer review to ensure that the team’s work reflects the industry’s best practices for data curation activities, including data privacy and anonymization standards.

• Ensure all datasets meet analysis-ready and privacy requirements by performing necessary data curation activities (e.g. pre-process, contextualize and/or anonymize).

• Ensure that datasets are processed to meet conditions mentioned in the approved data re-use request (e.g., remove subjects from countries that do not allow re-use). Write clean, readable code.

• Ensure that deliverables are appropriately quality controlled, documented, and when required, can be handed over to R&D Tech team for production pipeline implementation.

• Transforming raw healthcare data into products that can be used to catalyze the work of the wider RWDMA and Biostatistics teams and be leveraged by our diverse group of stakeholders to generate insights.

• Ensuring data quality, integrity, and security across various data sources.

• Supporting data-driven decision-making processes that enhance patient outcomes and operational efficiencies.

Education Requirements

Advanced degree (Master's or Ph.D.) in Life Sciences, Epidemiology, Biostatistics, Public Health, Computer Sciences, Mathematics, Statistics or a related field with applicable experience.

Job Related Experience

• Experience in data engineering and curation, with majority of experience on real-world data in the healthcare or pharmaceutical industry.

• Proven ability to handle and process large datasets efficiently, ensuring data privacy.

• Proficiency in handling structured, semi-structured, and unstructured data while ensuring data privacy.

• Understanding of data governance principles and practices with a focus on data privacy.

• Innovative mindset and willingness to challenge status quo, solution-oriented mindset

• Fluent in written and spoken English to effectively communicate and able to articulate complex concepts to diverse audiences

• Experience of working in global matrix environment and managing stakeholders effectively

• Experience in complex batch processing, Azure Data Factory, Databricks, Airflow, Delta Lake, PySpark, Pandas and other python dataframe libraries including how to apply them to achieve industry standards and data privacy.

• Proven ability to collaborate with cross-functional teams.

• Strong communication skills to present curated data.

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

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