Engineer

Bring more to life.

Are you ready to accelerate your potential and make a real difference within life sciences, diagnostics and biotechnology

At Pall Corporation, one of 15+ operating companies, our work saves lives-and we're all united by a shared commitment to innovate for tangible impact.

You'll thrive in a culture of belonging where you and your unique viewpoint matter. And by harnessing Danaher's system of continuous improvement, you help turn ideas into impact - innovating at the speed of life.

As a global leader in high-tech filtration, separation, and purification, Pall Corporation thrives on helping our customers solve their toughest challenges. Our products serve diverse, global customer needs across a wide range of applications to advance health, safety and environmentally responsible technologies. From airplane engines to hydraulic systems, scotch to smartphones, OLED screens to paper-everyday Pall is there, helping protect critical operating assets, improve product quality, minimize emissions and waste, and safeguard health. For the exponentially curious, Pall is a place where you can thrive and amplify your impact on the world. Find what drives you on a team with a more than 75-year history of discovery, determination, and innovation.

Learn about the which makes everything possible.

The Engineer role is responsible for applying advanced simulation and/or data-driven methods to solve complex filtration and separation challenges and expand digital capabilities across R&D. This role is designed for a CFD engineer or a data scientist/engineer, depending on candidate strengths, with opportunities to expand across domains. Regardless of background, the person in this role will partner closely with product development engineers, experimental scientists, and digital stakeholders to play a key role in transforming fragmented R&D data into scalable, well-governed, and searchable data assets that enable faster innovation and decision making.

In this role, you will have the opportunity to:

Develop data-driven models and machine-learning solutions using Python or similar programming languages leverage simulation tools (e.g., CFD using Ansys Fluent) where appropriate to generate actionable product and process insights Acquire, structure, and analyze experimental, simulation, and operational data ensuring high data quality, consistency, and usability across R&D systems Architect, design, and scale R&D data infrastructure on a modern platform such as Databricks or Snowflake, including ingestion pipelines (ETL), implementation of data governance practices (metadata management, data quality standards), and development of searchable datasets to enable model integration and broader digital transformation within R&D. Validate and refine models against experimental or operational data apply statistical analysis, engineering fundamentals, and sensitivity studies to identify key drivers, improve model accuracy, and strengthen confidence in recommendations. Communicate plans and technical findings clearly to cross-functional stakeholders through reports, dashboards, presentations, and collaborative discussions.

The essential requirements of the job include:

Master's or PhD in Mechanical Engineering, Chemical Engineering, Data Science, Computer Science, Applied Mathematics, or a related technical field. Multiple years of experience in data engineering, data science, scientific computing, CFD, or a closely related role in an applied industrial or R&D environment. Strong proficiency in data engineering or data science (Python, SQL, data pipelines, platforms such as Databricks/Spark) is highly desired experience with engineering simulation tools (e.g., Ansys Fluent, CAD) is also valuable. Foundation in data science and engineering fundamentals such as statistics, machine learning, database architecture, and scalable data processing, or a background in fluid mechanics, transport phenomena, heat transfer, or numerical methods. Strong communication skills, with fluency in English.

Travel, Motor Vehicle Record & Physical/Environment Requirements:

It would be a plus if you also possess previous experience in:

. Experience building and deploying data solutions on Databricks (e.g., Delta Lake, Spark), including ingestion pipelines, data modeling, or working with large-scale scientific or experimental datasets

. Familiarity with engineering or scientific domains (e.g., CFD, multiphase flow, porous media) and/or experience enabling analytics or modeling workflows on top of structured data platforms

Pall Corporation, a Danaher operating company, offers a broad array of comprehensive, competitive benefit programs that add value to our lives. Whether it's a health care program or paid time off, our programs contribute to life beyond the job. Check out our benefits at .

Join our winning team today. Together, we'll accelerate the real-life impact of tomorrow's science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life.

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