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Senior Data Management Programmer - Job Opportunity at Sanofi EU

Hyderabad, India
Full-time
Senior
Posted: July 10, 2025
On-site
Based on the senior-level requirements, pharmaceutical industry context, and Hyderabad location, the salary range is likely between INR 2,200,000 to INR 3,500,000 annually (approximately USD 26,000 to USD 42,000). This reflects the premium for advanced technical skills in SAS, R, Python, and AI/ML implementation, combined with the specialized pharmaceutical domain expertise required for this role.

Benefits

Comprehensive health insurance coverage providing financial security and peace of mind for medical expenses
Premium healthcare benefits including prevention and wellness programs that exceed standard market offerings
Generous gender-neutral parental leave policy of at least 14 weeks, significantly above industry standards
Well-crafted rewards package designed to recognize contributions and amplify professional impact
International career mobility opportunities with potential for global assignments and transfers
Continuous professional development programs and career advancement support

Key Responsibilities

Lead the development of sophisticated data validation systems, summary analytics, and advanced reporting solutions that directly impact clinical trial success and regulatory compliance
Design and deploy comprehensive data review frameworks that ensure data integrity across multiple therapeutic areas and external data sources
Architect automated protocol deviation identification systems that streamline compliance monitoring and reduce manual oversight requirements
Collaborate strategically with Data Reporting Analysts to optimize reporting infrastructure and maintain competitive advantage through enhanced analytical capabilities
Drive innovation in data visualization through Power BI, Spotfire, R/Shiny, and SAS solutions that transform complex clinical data into actionable insights
Lead technical documentation initiatives at Clinical Trial Technology level, establishing best practices and programming standards that influence organizational efficiency
Analyze emerging customer requirements and develop strategic technical solutions that position the organization at the forefront of clinical data management

Requirements

Education

Bachelor or Master of Science degree or above, preferably in a life science or mathematics-related area (e.g., Pharmaceutical, medical, or mathematics, computer science or similar technical fields)

Experience

At least 4 years' SAS programming experience, or have other equivalent programming language experience such as R/R shiny, Python, or have equivalent data visualization tools experience such as Spotfire, Power BI, Tableau

Required Skills

Advanced project management skill Advanced collaboration and communication skill Outstanding capability of independent thinking and delivery of accurate outcomes Meeting management skill such as organize meeting and discussion Crystal clear logical thinking Intercultural skills with ability to work effectively in a multi-cultural context Advanced expertise in programming language such as SAS, R, Python Advanced expertise in database structure and data flow Strong knowledge of industry standards and practices (e.g. CDISC especially CDASH and SDTM) Knowledge of data visualization tools such as Spotfire, Power BI, Tableau Experience in implementing and fine-tuning AI/ML model Strong knowledge of current regulatory guidelines, and GCP practices regarding Data Management Understanding of advanced drug development concepts such as Decentralized Clinical Trials (DCT), Master & Adaptive Protocols, eSource and AI Based automations
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Sauge AI Market Intelligence

Industry Trends

The pharmaceutical industry is experiencing a significant shift toward decentralized clinical trials (DCT) and AI-driven automation, creating unprecedented demand for data management professionals who can bridge traditional clinical research with emerging digital technologies. This transformation is accelerating post-COVID as companies seek to reduce costs while maintaining regulatory compliance and data integrity. Clinical data management is evolving from reactive data cleaning to proactive data quality assurance through real-time monitoring and predictive analytics. Organizations are investing heavily in professionals who can implement machine learning models for protocol deviation detection and automated data validation, representing a fundamental shift in how clinical trials are conducted. The integration of multiple data sources including wearable devices, electronic health records, and patient-reported outcomes is creating complex data ecosystems that require sophisticated programming skills and deep understanding of data flow architectures. This trend is driving demand for senior-level professionals who can manage these integrated systems effectively.

Role Significance

Typically leads or collaborates with 3-5 data management professionals including Data Reporting Analysts, junior programmers, and clinical data coordinators. May also interface with cross-functional teams of 10-15 members including clinical operations, biostatistics, and regulatory affairs teams.
This is a senior individual contributor role with significant technical leadership responsibilities. The position requires independent decision-making on complex technical challenges and serves as a subject matter expert for data management programming across multiple therapeutic areas. The role sits at the intersection of technical implementation and strategic business impact.

Key Projects

Implementation of AI-driven automated protocol deviation detection systems that can process complex clinical trial data in real-time Development of integrated data visualization platforms that combine multiple therapeutic area data sources for executive-level reporting Creation of standardized programming frameworks that can be deployed across global clinical trials to ensure consistency and compliance Design and implementation of decentralized clinical trial data management systems that accommodate remote patient monitoring and digital endpoints

Success Factors

Mastery of multiple programming languages and ability to select the optimal technology stack for specific clinical data challenges, ensuring both technical excellence and business value delivery Deep understanding of regulatory requirements and ability to translate complex compliance needs into automated technical solutions that reduce manual oversight while maintaining audit readiness Strong project management capabilities with proven ability to deliver complex technical solutions within clinical trial timelines, balancing speed with quality and regulatory compliance Excellent communication skills to bridge technical complexity with business stakeholders, ensuring that advanced analytical solutions are understood and adopted by clinical teams Adaptability to emerging technologies and regulatory changes in the pharmaceutical industry, with demonstrated ability to quickly learn and implement new tools and methodologies

Market Demand

High demand with limited supply of qualified candidates. The combination of advanced programming skills, pharmaceutical industry experience, and emerging technology expertise (AI/ML, DCT) creates a competitive market where organizations are actively seeking and retaining such professionals.

Important Skills

Critical Skills

Advanced SAS programming skills remain the foundation of pharmaceutical data management, with most regulatory submissions and clinical trial data processing still heavily dependent on SAS infrastructure and validated procedures Deep understanding of CDISC standards (CDASH, SDTM) is absolutely essential as these form the backbone of regulatory submissions and data exchange in pharmaceutical industry globally Project management capabilities are crucial given the complex, timeline-driven nature of clinical trials where delays can cost millions of dollars and impact patient access to new treatments Strong communication and collaboration skills are vital for success in the highly regulated pharmaceutical environment where cross-functional coordination and clear documentation are required for regulatory compliance

Beneficial Skills

AI/ML implementation experience provides significant competitive advantage as the pharmaceutical industry increasingly adopts these technologies for efficiency and insight generation Experience with modern data visualization tools like Power BI and Spotfire enhances ability to communicate complex data insights to non-technical stakeholders and executives Understanding of decentralized clinical trial concepts positions candidates for the evolving clinical research landscape post-COVID Python and R programming skills complement traditional SAS expertise and provide flexibility for emerging analytical requirements and integration with modern data science workflows

Unique Aspects

This role offers exposure to cutting-edge pharmaceutical technologies including AI/ML implementation in clinical trials, positioning the candidate at the forefront of industry innovation and digital transformation
The position provides opportunity to work across multiple therapeutic areas and global studies, offering diverse experience that is highly valuable for career advancement in pharmaceutical data management
The role combines technical programming expertise with strategic business impact, allowing for development of both deep technical skills and business acumen within a global pharmaceutical context
The emphasis on emerging technologies like decentralized clinical trials and AI-based automation provides exposure to the future of pharmaceutical development and competitive advantage in the job market

Career Growth

Progression to management roles typically occurs within 2-3 years given the senior level of current responsibilities and the high demand for experienced professionals in pharmaceutical data management. Movement to director-level positions generally requires 4-6 years of additional experience and demonstrated success in leading complex technical initiatives.

Potential Next Roles

Data Management Lead or Manager with responsibility for multiple therapeutic areas and larger teams of data management professionals Clinical Data Science Manager focusing on AI/ML implementation and advanced analytics across clinical development programs Director of Clinical Data Management with strategic oversight of global data management operations and technology roadmap Principal Data Scientist or Head of Clinical Data Analytics with responsibility for innovation and emerging technology adoption

Company Overview

Sanofi EU

Sanofi is a multinational pharmaceutical company headquartered in France and one of the world's largest pharmaceutical companies by revenue. The company operates in over 170 countries and focuses on prescription medicines, vaccines, and consumer healthcare products. Sanofi has been investing heavily in digital transformation and data analytics capabilities to accelerate drug discovery and development processes.

Sanofi ranks among the top 10 global pharmaceutical companies with strong market presence in key therapeutic areas including diabetes, oncology, immunology, and vaccines. The company's commitment to innovation is demonstrated through significant R&D investments and strategic partnerships with technology companies to enhance clinical trial capabilities.
The Hyderabad Hub represents Sanofi's strategic investment in India as a key market and talent center. This location serves as a crucial innovation hub supporting global operations, with access to high-quality technical talent and cost-effective operations while maintaining international standards for pharmaceutical development.
Sanofi promotes a collaborative, science-driven culture with emphasis on innovation and patient impact. The company's hub model encourages cross-functional collaboration and provides exposure to global pharmaceutical operations, offering excellent learning opportunities and career development in an international environment.
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