Senior Specialist, Scientific Software Engineer, Digital Insights, DSCS Digital Technologies (Hybrid)

Merck; Boston (MA); Vor Ort; USD 120.000 - 180.000; Vollzeit

Zusammenfassung

Merck is seeking a Senior Specialist, Scientific Software Engineer to join the Digital Insights team in Boston. The role focuses on designing and delivering scalable scientific software, data pipelines, and enterprise-grade platforms across drug development and analytical domains.

The successful candidate will collaborate with IT, security, data governance, and vendor teams to productionize prototype tools, ensuring robust data management and analytics-ready outputs for decision-making across

Aufgaben

• Provide software and data engineering expertise to build, scale, and sustain scientific and automation solutions, taking them from prototype to robust, secure, maintainable, enterprise-grade production software.
• Design and build reusable platforms, backend services, and APIs that unify analytical instrument and laboratory data, and consolidate fragmented or legacy tools into well-architected, scalable systems.
• Lead data engineering and data product development, designing and operating the pipelines, data models, and reusable data products that keep data reliable, well-structured, and analytics-ready for downstream decision-making.
• Partner effectively with IT, infrastructure, security, data governance, and vendor teams to deploy, integrate, and sustain solutions in production, navigating enterprise standards and requirements.
• Own end-to-end software delivery, including solution architecture, development, integration testing, documentation, deployment, and user acceptance; establish engineering best practices such as version control, code review, automated testing, and CI/CD.

Jobbeschreibung

Job Description

Role Summary:

We are seeking a Senior Specialist, Scientific Software Engineer to join our Digital Insights team within the Development Sciences and Clinical Supply Digital Technologies organization. Digital is the multiplier that will allow DSCS to deliver better experiments faster, efficient filing and launch, more robust supply chains and higher-confidence decisions across the portfolio.

The Development Sciences and Clinical Supply Digital Technologies organization is responsible for the invention and application of new digital tools/workflows to support scientists across drug substance development, drug product development and analytical development. We aspire to embed digital technologies into the fabric of DSCS culture to drive transformational impact. Our portfolio includes a growing set of high-impact scientific software, automation, and data solutions that begin as scientist-built prototypes and must be engineered into scalable, production-grade capabilities. In this Senior Specialist role, the successful candidate will provide the software and data engineering expertise needed to build, scale, and sustain these solutions and partner with IT teams to bring them into production, operating at the intersection of scientific software engineering, data engineering, and laboratory automation.

The successful candidate will own software and data engineering across our portfolio: designing and building reusable platforms, backend services, and APIs; developing robust data pipelines and data products that keep scientific and instrument data reliable, well-structured, and analytics-ready; and consolidating fragmented or legacy tools into secure, maintainable, enterprise-grade systems. Working closely with scientists and partnering effectively with IT, infrastructure, security, and vendor teams, the candidate will translate promising scientific tools into durable, scaled impact across the pipeline.

Responsibilities:

• Provide software and data engineering expertise to build, scale, and sustain scientific and automation solutions, taking them from prototype to robust, secure, maintainable, enterprise-grade production software.

• Design and build reusable platforms, backend services, and APIs that unify analytical instrument and laboratory data, and consolidate fragmented or legacy tools into well-architected, scalable systems.

• Lead data engineering and data product development, designing and operating the pipelines, data models, and reusable data products that keep data reliable, well-structured, and analytics-ready for downstream decision-making.

• Partner effectively with IT, infrastructure, security, data governance, and vendor teams to deploy, integrate, and sustain solutions in production, navigating enterprise standards and requirements.

• Own end-to-end software delivery, including solution architecture, development, integration testing, documentation, deployment, and user acceptance; establish engineering best practices such as version control, code review, automated testing, and CI/CD.