Senior Data Engineer

Bring more to life.

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

At SCIEX, one of Danaher’s 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 part of SCIEX, you will help to influence life-changing research and outcomes, while accelerating your potential. For more than 50 years, we have been empowering our customers to solve the most impactful analytical challenges in quantitation and characterization through ground-breaking innovation and outstanding reliability and support. You will be part of a winning team, enabled by DBS, that is passionate about helping life science experts around the world get to answers they can trust.

Learn about the Danaher Business System, which makes everything possible.

The Senior Data Engineer is responsible for delivering complete, accurate, and trusted data from multiple source systems into the Azure Data Warehouse and modern analytics platforms. This role partners closely with business stakeholders to enable data‑driven decision‑making through business analytics and advanced data platforms.

This position is part of the Global IT organization supporting SCIEX, Molecular Devices, and the Life Sciences Platform. This position reports to the Senior Manager - IT Applications and will be fully remote from India.

In this role, you will have the opportunity to:

- Partner with business stakeholders to design and deliver scalable data warehouse and analytics solutions

- Design, develop, and optimize data pipelines, orchestration workflows, and database objects across Azure SQL, Snowflake, and Microsoft Fabric environments

- Monitor, troubleshoot, and improve data pipeline reliability and performance in production environments

- Drive continuous improvement initiatives across data architecture, ETL/ELT processes, and development standards

- Maintain data models, technical documentation, and version control practices, ensuring alignment with enterprise standards