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

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.

Collaborate closely with scientists, data scientists, and cross-functional stakeholders to translate scientific needs into durable software, and provide technical leadership during onboarding, training, and production rollout to reduce key-person dependencies.

Demonstrate excellent interpersonal, communication, and collaboration skills.

Embrace and model our core values, including fostering a supportive culture where all can thrive.

Be able to effectively collaborate in a dynamic, integrated, and multidisciplinary team environment.

Demonstrate a clear ability to perform impactful technical innovation in a team-oriented manner that builds trusted partnerships across vast stakeholder networks.

Education Minimum Requirement:

Ph.D. in Computer Science, Data Science, Software Engineering, Chemistry, Physics, Engineering, Pharmaceutical Sciences, or a closely-related field.

M.S. in Computer Science, Data Science, Software Engineering, Chemistry, Physics, Engineering, Pharmaceutical Sciences, or a closely-related field with at least 2 years of industrial/pharmaceutical or relevant experience.

B.S. in Computer Science, Data Science, Software Engineering, Chemistry, Physics, Engineering, Pharmaceutical Sciences, or a closely-related field with at least 4 years of industrial/pharmaceutical or relevant experience.

Required Experience and Skills:

Deep software development expertise, with hands-on experience building production-grade applications, backend services, and APIs using Python and/or equivalent languages.

Demonstrated experience scaling and hardening software from prototype to production, including architecting reusable platforms and modernizing or consolidating legacy or fragmented tools.

Experience partnering with IT, infrastructure, security, and/or data governance teams to deploy and sustain software in production within enterprise standards.

Strong data engineering skills, with demonstrated experience designing, building, and operating production data pipelines (ETL/ELT), data models, and data products, including working with databases, data warehouses, or data lakes.

Experience developing software integrations with scientific instruments, laboratory systems, or external platforms via APIs, SDKs, or file-based interfaces.

Experience with software engineering best practices, including version control (e.g., Git), automated testing, code review, and CI/CD.

Ability to translate complex scientific requirements into robust, maintainable software, and to communicate technical concepts clearly to non-technical audiences; strong written and verbal communication skills.

Preferred Experience and Skills:

Software and data engineers with experience supporting pharmaceutical development (e.g., drug substance, drug product, or analytical development) are strongly preferred.

Hands-on experience integrating analytical instrument software and chromatography data systems, including building data-ingestion pipelines from instrument sources.

Experience integrating with laboratory informatics ecosystems and ELN/LIMS platforms (e.g., Signals).

Familiarity with high-throughput screening and experimentation workflows and the data they generate.

Experience with scientific data standards and FAIR data principles, including standardized data formats and long-term data archival.

Experience building and delivering data products in a scientific or laboratory context, and familiarity with data engineering tooling and orchestration frameworks.

Experience developing user-facing web applications that surface scientific data and workflows.

Familiarity with cloud platforms and containerization.

Knowledge of data governance, data lineage, and validation frameworks in regulated (e.g., GxP) environments.

Prior contributions to cross-functional software deployments, user training, and production support are a strong plus.

# eligibleforERP

#PRD

Required Skills:

Analytical Acumen, Big Data, Computer Science, Data Engineering, Data Format, Data Ingestion, Data Lake, Data Modeling, Data Pipelines, Data Science, Dataset Management, Data Standards, Data Structures, Intellectual Curiosity, Manufacturing Scale-Up

Preferred Skills:

Current Employees apply HERE

Current Contingent Workers apply HERE

US and Puerto Rico Residents Only:

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.

As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristi