Job
Description
Bridge business needs with technical solutions by leading IT application design and implementation. Collaborate with partners to define and deliver requirements, translating them into detailed specifications. Own the technical vision of products and compile detailed technical designs, refining user Epics/stories. Optimize performance, mitigate risks, and ensure alignment to timelines and resource allocations. Advise on industry trends and standard methodologies to enhance performance and business outcomes. Provide technical direction and guidance to IT teams and business units. Contribute to Data & Software Engineering standards and best practices. Research new technologies to boost system performance and scalability. Lead and mentor technical teams (Data Engineering, Cloud Engineering, Software Engineering) and work with AI/GenAI leads to foster collaboration and innovation. Ensure platform stability, scalability, and simplicity while adhering to regulatory requirements and data security standards. Foster continuous improvement and innovation. Oversee technical leadership throughout the software development lifecycle and provide hands-on support in development, technical delivery, review, and testing while collaborating with global teams. Apply central Enterprise Data Platforms and guide DevOps, DataOps, and MLOps teams to ensure standard methodologies. Ensure data solutions stay in sync with FAIR principles and support end-to-end data science and machine learning. Essential Skills/Experience Minimum 10+ years in developing and delivering software engineering and data engineering solutions. Strong problem-solving skills with a focus on high-quality solutions. Deep technical expertise in data engineering, cloud patterns (e.g., microservices, serverless), and software engineering principles. Proficiency in containerization (Docker, Kubernetes), databases (SQL, NoSQL), CI/CD pipelines, and automated deployment tools. Leadership experience in mentoring and team management. Fluency in Python and Java; knowledge of security and data protection. Familiarity with DevOps tools, DataOps principles, and Data Mesh concepts. Hands-on experience with AWS Compute Services, Apache Airflow, Snowflake, Power BI, and NodeJS. Strong understanding of AI Engineering and implementation of AI/ML models using Amazon SageMaker. Experience in Agile methodologies and product development/management. Desirable Skills/Experience Bachelors or masters degree in health sciences, Life Sciences, Data Management, IT, or a related field. Experience in the pharmaceutical industry or a similar multinational environment. AWS Cloud or relevant data/software engineering certifications. Awareness of use case specific GenAI tools available in the market and their application in day-to-day work scenarios. Working knowledge of basic prompting techniques and commitment to continuous improvement of these skills. Ability to stay up to date with developments in AI and GenAI, applying new insights to work-related situations.
