Data Engineer

We are seeking a talented and highly motivated data engineer to join the Quantitative Sciences & Digital Transformation group within the Portfolio Integration & Business Operations organization. The candidate will work closely with data scientists, statisticians, Biologics Development (Client) scientists, and IT partners to develop and implement data infrastructure, data pipelines, and tools for the collection, cleaning, verification, structuring, visualization, and analysis of large amounts of historical and new data.
The primary goal of this role is to enable advanced analytics and modeling by providing high-quality data that is easily accessible and usable. The candidate should have experience in designing and implementing data solutions, as well as a strong understanding of data architecture and data modeling.
The candidate should be able to work effectively in a matrix team environment and have excellent communication skills. They should be able to collaborate with stakeholders across the Biologics Development network to understand their data needs and provide solutions that meet those needs.

Responsibilities:
Establishes data infrastructure and scalable solutions to efficiently collect, organize, clean, verify, analyze, and
visualize data from multiple data sources.
Contribute to testing, quality assurance, and documentation of data pipelines and systems
Provides data engineering and programming support to Client projects, including data visualization, data mining,
data trending, and prediction based on large historical data for process, analytical and cell line development.
Provides guidance, consultations, and training to Client scientists on data engineering and data science related
topics. Promote digital-first mindset and data-driven decisions.
Contributes to digital transformation, modeling and automation efforts across the Biologics Development
organization

Education and

Qualifications:

Bachelor's degree in Data Science, Computer Science, Software Engineering, or relevant majors with significant
training and experience in data engineering Required. Master's Degree Preferred
In-depth knowledge of database architecture and design
Proficient in programming languages such as Python, R, SQL, Java, or Scala and in debugging and diagnosing
issues
Expertise with data visualization tools such as Spotfire, Tableau, RShiny

App or Python Dash

Experience with big data technologies such as Hadoop, Spark, or Hive is a plus
A background in biologics development or pharmaceuticals is strongly preferred.
Knowledge of electronic laboratory notebook systems and laboratory data management systems is highly
desired.
Demonstrated ability to understand business needs and clearly communicate technical concepts to audiences
with diverse scientific backgrounds.
Able to work independently or as a team member to meet goals, objectives, and commitments.