Job Description

The Scientific Digital and Tech organization part of R&D Digital & Tech is an integrated family that powers the GSK R&D discovery, manufacture, and supply of new medicines and vaccines to patients. It focuses on optimizing CMC, informing Vaccine and Medicine design, and delivering a modern laboratory experience.

Scientific Data Engineering is a new organization responsible for enterprise data and architecture, providing thought process and architecture services for all aspects of data across the Scientific area. This includes the use of, and augmentation to, the two GSK data platforms on GCP and Azure, design and creation of data pipelines to surface data as a \xe2\x80\x9cproduct\xe2\x80\x9d in a data Mesh architecture across two platforms.

We are looking for a highly skilled and experienced Senior Data Engineer to join our growing CMC Data Engineering team. This software practitioner will work with a team of talented data engineers focused on building data as products following data mesh architecture for CMC. They will drive scale and automation by providing expert technical skills and implementing cloud-based data ingestion and processing patterns i.e., \xe2\x80\x98end to end data workflows\xe2\x80\x99 to address specific \xe2\x80\x98data as a product\xe2\x80\x99 requirements. This team would partner closely with the Platforms and Data Architecture and Domain functions.

The Senior Data Engineer will contribute to the design, development, testing and release of pipelines, workflows, microservices, within a well-defined architecture and detailed specification. They will carry out common maintenance and support tasks on existing data services.

This role will provide YOU the opportunity to lead key activities to progress YOUR career, these responsibilities include some of the following\xe2\x80\xa6

Using Azure cloud services and GSK data platform tools to ingest, egress, and transform data from multiple sources.

Optimize the design and execution of complex solutions in data ingestion and data transformation.

Produces well-engineered software, including appropriate automated test suites, technical documentation, and operational strategy

Provides input into the roadmaps of upstream teams (e.g., Data Platforms, DataOps, DevOps) to help improve the overall program of work

Ensure consistent application of platform capabilities to ensure quality and consistency concerning logging and lineage

Fully versed in coding best practices and ways of working, and participates in code reviews and partnering to improve the team\xe2\x80\x99s standards

Adhere to QMS framework, Security & Regulatory Standards, and CI/CD best practices and helps to guide improvements to them that improve ways of working

Provide mentoring to team members to help others get the job done right.

Guiding engineering teams in the adoption and creation of data Mesh best practices.

Maintains best practices for engineering and architecture on our Confluence site.

Engage in experimentation and innovation to drive relentless improvement.

Why you?

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:

Bachelor\xe2\x80\x99s Degree in Computer Science

4+ years of experience in data engineering

3+ years\xe2\x80\x99 experience with MS Azure Cloud

2+ years\' experience with Azure Databricks

2+ years\xe2\x80\x99 experience with Python

Preferred Qualifications:

If you have the following characteristics, it would be a plus:

MS in computer science

Hands-on experience with Azure Data Analytics services e.g., ADLS, Azure Data Factory, Azure Databricks, Purview, Azure Synapse, etc.

Data Platforms and Domain-driven design.

Agile, DevOps & Automation [of testing, build, deployment, CI/CD, etc.]

Data analytics & data quality/integrity

Testing strategies & frameworks

Good knowledge of various software paradigms: domain-driven, procedural, data-driven, object-oriented, functional

Familiar with Big Data technologies like Spark, Hadoop.

Familiar with Java or Scala

Demonstrable knowledge depth in more than one area of software engineering and technology

Track record of applying best data and software engineering practices in Pharma CMC and Scientific domains.

Known for excellent, rigorous software engineering with full stack role including DevOps on a development team

Experience in applying data curation, virtualization, workflow, and advanced visualization techniques to enable support across multiple products and assets to drive results across R&D business operations.

Experience in building products with modern Cloud architectures, platforms, and back-end systems

#LI-GSK

Why Us?

GSK is a global biopharma company with a special purpose \xe2\x80\x93 to unite science, technology and talent to get ahead of disease together \xe2\x80\x93 so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns \xe2\x80\x93 as an organization where people can thrive. Getting ahead means preventing disease as well as treating it, and we aim to positively impact the health of 2.5 billion people by the end of 2030.

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it\xe2\x80\x99s also about making GSK a place where people can thrive. We want GSK to be a workplace where everyone can feel a sense of belonging and thrive as set out in our Equal and Inclusive Treatment of Employees policy. We\xe2\x80\x99re committed to being more proactive at all levels so that our workforce reflects the communities we work and hire in, and our GSK leadership reflects our GSK workforce.

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