Process Research and Development invents chemical processes and prepares the active pharmaceutical ingredient to enable clinical trials, toxicology studies and drug product development for AbbVie’s pre-clinical and clinical drug pipeline. We create valuable intellectual property through composition of matter, chemical processes and technologies resulting in cost effective commercial manufacturing processes. We develop the supply chain for APIs, prepare and defend CMC (Chemistry, Manufacturing and Control) regulatory content.
The Process Engineering group within AbbVie's Process R&D organization works in multi-functional teams to develop scalable processes and supply active pharmaceutical ingredient for safety testing, clinical trials, and formulation development. Early in development, engineers focus on ensuring the process can be run safely, identifying and addressing major scale-up issues and developing the final chemical process step. Later in development, engineers optimize the chemical process and lead manufacturing campaigns in the R&D Pilot Plant. In the final stage of development, engineers transfer the optimized process to commercial manufacturing and support Process Validation. Throughout the development lifecycle, lab automation, data analysis and data management play a significant role in gaining organizational efficiency and generating scientific insights.
The Data Engineer will play a key role in the automation and digitalization initiatives at AbbVie as we continue our transformation towards Pharma 4.0. The vision of the automation team is to transform the culture and the way we do research to enhance safety, access new enabling capabilities, and gain efficiency in development of life changing medicines with high quality data through a deliberate and sustainable automation competency. The tools generated by this role will be instrumental in supplying and structuring findable accessible interoperable and reusable (FAIR) data, data analytics, and data visualization to scientists, allowing them to reduce risk and make faster decisions that directly impact drug pipeline development. The work will also provide a strong foundation for the continued development of digital modeling and machine learning workflows.
We are seeking an experienced Data Engineer who will support automation and information management efforts within Process R&D. These efforts include the development of automated and robust data pipelines from point of production from equipment and measurement devices to their ultimate destinations, data modeling, front-end and back-end development of supporting information management tools, development of application programming interfaces (APIs), continuous integration and continuous delivery (CI/CD), as well as appropriate data analytics. Ideal candidates should possess a BS/MS degree in a discipline with a substantial software programming component and/or have developed the requisite experience in previous roles. Previous experience in pharma is preferred but not necessary.
- Deliver fit-for-purpose solutions using out-of-the-box and innovative thinking to address data related challenges in pharmaceutical development.
- Work cross-functionally to build web-based data management solutions that will require diverse development skills, such as front-end, back-end, API, and dashboard development as well as data modeling.
- Bring data to life through dynamic and interactive dashboards and visualizations.
- Build robust, clean, and automated end-to-end data pipelines, e.g., from instrument measurement to a data warehouse.
- Practice continuous delivery and deployment to enable an agile framework.
- Partners with Information Research to develop and deploy scalable and maintainable solutions.
- Partners with Process R&D scientific & technical staff to understand business challenges and effectively guide toward sustainable solutions.
- BS or MS in a STEM discipline with at the least 4 years of pertinent experience in the coding, data analysis and visualization.
- Experience carrying software tools through design, implementation, and deployment.
- Should be proficient in programming languages and frameworks, such as Bash, Python, Django, Plotly DASH, SQL, Flask, and HTML/CSS.
- Experience with tools enabling CI/CD e.g., git, docker, pipelining tools is preferred.
- Experience in accessing instrument data through serial connections is desired.
- Ability and desire to quickly learn and apply different technologies is a must.
- Familiarity with equipment controls and communication protocols are a plus.
- Builds strong relationships with peers and cross functionally with partners outside of team to enable higher performance.
- Proactively learn and venture into new areas of business interest.
- Act as a strong team player in a cross functional collaborative environment thriving for world class excellence.
- Learns fast, grasps the "essence" and can change course quickly where indicated.
- Raises the bar and is never satisfied with the status quo.
- Creates a learning environment, open to suggestions and experimentation for improvement.
- Embraces the ideas of others, nurtures innovation and manages innovation to reality.
- Demonstrate excellent communication skills and specifically.
- Illustrate strong oral and written technical communications.
- Seamlessly present data engineering solutions to multifunctional teams.
- Educate and train colleagues on various tools and techniques
Significant Work Activities: Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)
Travel: Yes, 5 % of the Time
Job Type: Experienced