Job Summary

Build the data foundation that helps us get to an AI native state Advanced AI is only as powerful as the data that enables it.

We are seeking an early-career Data Engineer passionate about creating high-quality scientific data products and contributing to the development of data fabric to support advanced analytics, AI, machine learning, and scientific decision-making across Pharmaceutical Product Development.

The ideal candidate will be an engineer who sees data not as a collection of tables, but as a strategic asset that powers scientific discovery and AI innovation. This role will provide an chance to work on complex datasets, modern cloud technologies, and cutting-edge digital transformation initiatives, with applications across chemical process development, biologics development, drug product development, and analytical development.

What You Will Do

- Build scientific data products for product development focused on datasets for molecular features, material properties, laboratory data, process and manufacturing parameters, stability and product performance data.
- Contribute to initiatives for data structuring and data contextualization.
- Develop and maintain scalable data pipelines supporting analytics, AI, and scientific modelling initiatives.
- Transform raw scientific and operational data into trusted, model-ready data products.
- Work with cross-functional teams to improve data accessibility, reliability, and quality.
- Support enterprise initiatives involving Databricks, Data Fabric, and cloud-native architectures.




- Automate data workflows and reduce manual effort through engineering best practices.
- Contribute to development of reusable data assets supporting Product Development innovation across US, Europe and India.

What Makes You Successful

You are naturally curious and:
- Ask why before asking how.
- Investigate root causes rather than treating symptoms.
- Enjoy solving messy, ambiguous data problems.
- Balance technical rigor with practical execution.
- Work effectively with scientists, analysts, data scientists, and engineers.

Qualifications

- Bachelors or Master s degree in Computer Science, Chemical Engineering, Information Systems, Bioinformatics, Biotechnology or related field with 2+ years of industry experience.
- Technical hands-on experience with modern data technologies.

Skills

- SQL
- Python
- ETL/ELT Development
- Delta Lake
- Databricks
- dbt
- Data Product Design
- Data Quality Engineering
- Data Observability

Preferred

- Experience working with pharmaceutical product development datasets in the scientific, manufacturing, or laboratory data domains
- Exposure to scientific, analytical, or laboratory-based methods through academic coursework, research with an aptitude for understanding the data generated by these techniques
- Familiarity with Data products and AI/ML workflows
- Experience with PySpark, Python, SQL, dbt, Databricks

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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