Associate Director - Enterprise Data & Analytic Platform Operation

Ready to help shape the future of healthcare?

GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organization where people can thrive. Getting ahead means preventing disease as well as treating it, and we aim to impact the health of 2.5 billion people around the world in the next 10 years.

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

GSK is expanding its presence in India with a new world-class Global Capability Centre (GCC) in Bangalore. Our ambition is to bring together the best and brightest minds, ready to join us in our work to improve the lives of patients and consumers around the globe.

We are determined to drive the extensive transformation to make global functions world-class and processes simple and easy to provide excellent user satisfaction to Employees, clients and vendors.

This role is to work with a diverse team of senior professionals to drive GSK's Enterprise Data & Analytics Platform Team.

Job Purpose: We are seeking a highly motivated and detail-oriented Data & Analytics Operations Specialist to join our dynamic team. The ideal candidate will have a strong background in data management, analytics, cloud technologies, financial operations (FinOps), data & analytics platforms, production support, data leadership skills, Data and AI skills, and risk and compliance. They should have a passion for leveraging data to drive business insights and efficiencies.

Key Responsibilities:

Data Management:

• Manage and maintain data infrastructures, ensuring data integrity, accuracy, and accessibility.
• Develop and implement data governance policies and procedures to ensure compliance with regulatory requirements.
• Oversee data collection, storage, and retrieval processes, ensuring data quality and consistency.

Analytics:

• Collaborate with cross-functional teams to identify data and analytics needs and develop solutions to support business objectives.
• Design and implement advanced analytics models and algorithms to uncover insights and drive decision-making.
• Utilize data visualization tools to create reports and dashboards that effectively communicate findings to stakeholders.

Cloud Technologies:

• Manage cloud-based data platforms (e.g., AWS, Azure, Google Cloud), ensuring optimal performance and scalability.
• Implement best practices for cloud data storage, security, and cost management.
• Coordinate with IT and other departments to integrate new cloud technologies and tools into existing systems.

Financial Operations (FinOps):

• Monitor and optimize cloud spending, ensuring cost-effective use of resources.
• Develop and implement financial management practices for cloud operations.
• Provide regular financial reports and insights to stakeholders, helping to drive budgetary decisions.

Data & Analytics Platforms:

• Manage and optimize data & analytics platforms to ensure they meet the needs of the business.
• Maintain and enhance platform capabilities to support data integration, processing, and analysis.
• Ensure the platforms are scalable, secure, and compliant with industry standards and regulations.

Production Support:

• Provide ongoing support for data and analytics platforms in a production environment.
• Monitor system performance, troubleshoot issues, and implement fixes to ensure minimal downtime.
• Develop and maintain documentation for production support processes and procedures.
• Coordinate with IT and other departments to ensure timely resolution of production issues.

Operations:

• Optimize data and analytics workflows to improve efficiency and reduce operational costs.
• Monitor and troubleshoot data pipelines and analytics platforms, ensuring seamless operation and minimal downtime.
• Coordinate with IT and other departments to integrate new technologies and tools into existing systems.

Data Leadership:

• Provide strategic direction for data management and analytics initiatives, aligning with organizational goals.
• Mentor and train team members on data best practices, tools, and technologies.
• Foster a culture of data-driven decision-making within the organization.
• Lead data-focused projects and initiatives, ensuring successful implementation and adoption.

Data and AI:

• Implement and manage AI and machine learning models to enhance data analytics capabilities.
• Leverage AI tools and techniques to automate data processes and generate predictive insights.
• Stay updated on the latest advancements in AI and machine learning and apply them to relevant business challenges.
• Collaborate with data scientists and AI specialists to integrate AI solutions into existing data platforms.

Risk and Compliance:

• Ensure data management and analytics practices comply with relevant regulations, industry standards, and corporate policies.
• Develop and implement risk management strategies to mitigate potential data-related risks.
• Conduct regular audits and assessments to identify and address compliance gaps.
• Collaborate with legal, compliance, and security teams to ensure data protection and privacy.
• Maintain up-to-date knowledge of regulatory changes and their impact on data management practices.

Collaboration & Communication:

• Work closely with stakeholders to understand their data, analytics, and financial requirements and provide actionable insights.
• Communicate complex data concepts in a clear and concise manner to non-technical audiences.
• Foster a culture of data-driven decision-making within the organization.

Qualifications:

• Bachelor’s degree in Data Science, Computer Science, Information Technology, or a related field. Master’s degree preferred.
• Overall 15 + years of IT experience, with hands on experience on Data and Analytics platforms.
• Well versed with Cloud technologies.
• 10+ years of experience in data management, analytics, cloud technologies, financial operations, data & analytics platforms, production support, data leadership, Data and AI, or risk and compliance.

At GSK we value diversity (Gender, LGBTQ +, PwD etc.) and treat all candidates equally. We aim to create an inclusive workplace where all employees feel engaged, supportive of one another, and know their work makes an important contribution.

#LI-GSK

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

  
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