18 annunci per il ruolo di & data solution architect - nova milanese, lom (recruiting in corso)

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- 70.000 € - 110.000 € all'anno
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- Inglese
- Laurea magistrale
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Broadcom —Milano, Lombardia
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Docebo —Milano, Lombardia
- Tempo pieno
- Spagnolo
- Inglese
- Laurea magistrale
Senior AI Engineer (f/m/d)
Awin —Milano, Lombardia
- Remoto
- AWS
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- Tirocinio formativo/stage
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Thales —Gorgonzola, Lombardia
- Tempo pieno
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- Ingegneria
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Director, HR Business Partnership (Technology and Product)
Docebo —Milano, Lombardia
- Tempo pieno
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Pairwise —Milano, Lombardia
- Tempo pieno
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- Dottorato di ricerca
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ACPV Architects —Milano, Lombardia
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BIM Technician
ACPV Architects srl —Milano, Lombardia
- Inglese
- Laurea magistrale
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Candidatura rapida
Dynamics 365 Customer Engagement – Customer Insights
Concentrix —Cernusco sul Naviglio, Lombardia
- Tempo pieno
- Gestionale
- Inglese
- Competenze analitiche
Manager, Customer Success
Docebo —Milano, Lombardia
- Tempo pieno
- Gestionale
- Inglese
- Laurea triennale
Electrical Engineer – Data Centers & Critical Facilities
AECOM —Milano, Lombardia
- Tempo pieno
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Thales —Gorgonzola, Lombardia
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ACPV Architects —Milano, Lombardia
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Bosch Group —Milano, Lombardia
- Tempo pieno
- Gestionale
- Project management
- Leadership
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LIFE SCIENCES SOLUTIONS ENGINEER
Philogen —Milano, Lombardia
Positioning within the salary range will be determined based on objective and neutral criteria, taking into account the candidate’s skills, experience, and the…
70.000 € - 110.000 € all'anno
22 ore
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LIFE SCIENCES SOLUTIONS ENGINEER

Philogen -
Milano, Lombardia

Candidati adesso

Dettagli della posizione

Tempo pieno
70.000 € - 110.000 € all'anno
22 ore fa

Qualifiche

Gestionale
Distribuzione software
Inglese
Laurea magistrale
SQL
RBAC
Python

Descrizione completa della posizione

Location: Milano - Italy

Department: Others

About Philogen

Philogen S.p.A. is a biotechnology company dedicated to developing targeted products for the imaging and treatment of life-threatening diseases, with a strategic focus on oncology. Our mission is to translate cutting-edge scientific innovation into effective therapies that improve patients’ lives.

Position Overview

We are looking for a Life Sciences Solutions Engineer who combines strong coding skills with deep expertise in at least one of the following areas:

Pharmaceutical quality systems or quality control.
GxP, computerized-system compliance, or regulated software validation.
Clinical trial operations, clinical data management, or trial oversight.

This is not a documentation-only compliance role. You will inspect data, write code, configure and test systems, and work directly with engineers, clinical teams, quality specialists, and business stakeholders. You will guide the introduction of production-grade AI and data systems into regulated workflows.

What You Will Do

Translate pharmaceutical and clinical requirements into implementable data models, workflows and access rules.
Guide software deployment through the applicable quality, privacy, security, and regulatory requirements.
Determine which regulatory frameworks apply to each use case rather than treating every healthcare system as subject to identical controls.
Analyze clinical trial data covering studies, sites, subjects, visits, forms, observations, queries, reviews, medical coding, and audit history.
Define and test controls for sensitive information, including role-based access, separation of duties, approvals, and audit trails.
Produce and maintain documentation such as intended-use definitions, risk assessments, traceability matrices, validation plans, test evidence, operating procedures, and change records.
Work with quality, clinical, security, legal, and engineering stakeholders to resolve differences between written procedures and actual system behavior.
Support technical workshops, deployment planning, validation, training, and post-deployment reviews.

What We Are Looking For

5+ years of professional experience in software engineering, data engineering, solutions architecture, technical consulting, or a comparable hands-on technical role.
Deep professional expertise in at least one of pharmaceutical quality, regulated computerized systems, or clinical trials.
Strong coding skills, preferably in Python, together with practical SQL and data-modeling experience.
Ability to understand complex data pipelines and trace how a source record is transformed, connected, exposed, and audited.
Ability to communicate effectively with software engineers and specialists from quality, clinical operations, data management, and compliance.
Experience in a pharmaceutical, biotechnology, healthcare, CRO, technology consultancy, or regulated cloud/software environment.
Strong professional English and the ability to produce precise technical and validation documentation.
High daily engagement with modern AI tools and an interest in the responsible deployment of agent-based systems.

Relevant Areas of Expertise

Candidates are not expected to know every framework below, but should have substantial practical experience in those relevant to their previous work:

ICH Good Clinical Practice and clinical trial data governance.
GxP and pharmaceutical quality systems.
Computerized-system validation and risk-based Computer Software Assurance.
EU Annex 11 and FDA 21 CFR Part 11.
GDPR and health-data access controls.
ALCOA+ data-integrity principles.
Clinical data management, electronic data capture, source-data review, clinical queries, coding, and trial audit trails.
EU medical-device or software regulation where applicable to a system’s intended use.
Quality risk management, change control, deviation management, CAPA, and supplier qualification.

Nice to Have

Experience delivering infrastructure, data, or AI platforms for pharmaceutical customers.
Familiarity with clinical data standards such as CDISC ODM, SDTM, or ADaM.
Experience with electronic data-capture systems, clinical trial management systems, quality-management systems, laboratory systems, or regulatory document platforms.
Knowledge of cloud security, Kubernetes, identity management, RBAC, and infrastructure-as-code.
Experience with knowledge graphs, ontologies, AI agents, retrieval systems, or governed generative-AI deployments.
Experience participating in audits, inspections, validation reviews, or regulated customer-qualification processes.
A professional background as a software engineer, data engineer, or solutions architect before specializing in life sciences.

Education

Master’s degree in Computer Science, Engineering, Data Science, Life Sciences, Biotechnology, Pharmaceutical Sciences, or a related field.
A mixed technical and life-sciences background is strongly preferred.
Strong academic credentials with international exposure.

What We Offer

Full-time employment.
Competitive gross annual salary ranging from €70,000 to €110,000 RAL. Positioning within the salary range will be determined based on objective and neutral criteria, taking into account the candidate’s skills, experience, and the level of responsibility associated with the role, as assessed throughout the selection process.
A hands-on role at the intersection of software engineering, clinical operations, and pharmaceutical compliance.
The opportunity to define how AI-enabled systems are validated and introduced into regulated workflows.
Direct exposure to leadership and high-impact projects across Philogen.
The opportunity to contribute to applied AI across both operational and scientific workflows.
A fast-moving, engineering-driven environment focused on real delivery rather than prototypes.

Job Location

Milan, Italy.

We invite interested candidates to submit their applications expressly authorizing the processing of personal data in accordance with Legislative Decree 196/2003. Our recruitment adheres to the provisions of Legislative Decree 198/2006, and we welcome applications from candidates of any gender orientation or expression, sexual orientation, age, ethnicity, or religious belief.
In compliance with Directive (EU) 2023/970 and Italian Legislative Decree No. 96 of 7 May 2026, this job advertisement has been drafted using gender-neutral criteria.

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