Manager / Senior Manager- Business Analytics and Engineering Governance

Role Overview:

The manager/ Senior Manager-Business Analytics and Engineering Lead will be responsible for leading and managing the business analytics engineering function, ensuring data readiness and quality to support transformation and AI initiatives. This role will play a critical part in establishing robust data management practices and driving data-driven decision-making across the organization.

Key Responsibilities:

• Lead the analytics and data engineering functions to support business transformation and AI initiatives.
• Research and Innovation: Stay up to date with the latest AI advancements, research new technologies (e.g., generative AI, large language models), and propose innovative solutions to drive growth.
• Manage the inventory of commercial data assets to ensure data readiness, quality, and accountability in alignment with risk, compliance, and regulatory guidelines.
• Collaborate with internal stakeholders, including DevOps, DataOps, Cyber Security, Risk, and Assurance teams, as well as the Commercial Leadership Team, to ensure adherence to best practices and governance standards.
• Establish and maintain a solution-oriented, well-structured data inventory to support analytics, reporting, and business insights.
• Drive continuous improvement in data management processes, ensuring data integrity and accessibility for business users.
• Support the development of scalable data solutions that align with organizational goals and technology strategies
• Documentation: Document the design, development, and deployment processes, as well as the solution architecture.
• Collaboration: Work closely with cross-functional teams including data scientists, software engineers, product managers, and stakeholders to define project goals and ensure AI solutions align with business objectives.
• Deployment Support: Deploy AI solutions into production environments, often by creating APIs and microservices that integrate with other applications and systems

Development:

• Strong working knowledge of Azure services and components, and the ability to stitch together various components towards a scalable, reliable and sustainable enterprise solution.
• Production experience delivering CI/CD pipelines across Azure and vendor products.
• Key knowledge of architectural patterns across code and infrastructure development.
• Contribute towards the design and development of the enterprise standards.
• Ensure project goals are achieved with quality and on time in alignment with the stakeholders' expectations.
• Ability to work on complex projects and in a distributed environment.
• Work in close collaboration with other team members in the Digital Dule organization and DevOps team to ensure Development/Delivery aspects are well represented in the project's requirements and deliverables.

Methodology:

• Incorporate agile ways of working
• Lead with modern data design and test driven development.
• Individuals will work as part of a product-centric delivery team(s) that will deliver value independently while fully embracing integrated DevOps approaches.
• Take ownership of the delivery/development projects and help steer until completion.

Governance

• Maintain governance that allows projects and stakeholders to manage overall project performance and manage program risks within the global nature of some of the programs.

Forward looking:

• Remain flexible towards technology approaches to ensure we are taking advantage of new technologies.
• Keep abreast of industry developments in analytics and interpret how these would impact services and present new opportunities.
• Quality, Risk & Compliance:
• Ensure all risks and issues associated with owned projects are promptly recorded and managed in the appropriate Risk & Issue logs.
• Ensure all Risks and Issues have clear action/mitigation/contingency plans defined, named action owners, and timelines for completion.

Technical Architecture:

• Design and Development of AI Models: Design, develop, train, and test machine learning (ML) models and algorithms to solve complex business problems.
• Be conversant with technical architecture to contribute to design discussions in partnership with the Delivery/Development Lead and dedicated Analytics

Key Technical skills and experience required:

• Overall 8 to 12 years of professional experience with Bachelor's or Master's degree in Computer Science, Engineering, Data Science etc.
• An ideal candidate would have an impressive hands-on work history in an advanced, recognized, and innovative environment.
• Data engineering experience and seasoned coder in the relevant languages: Python, SQL, Scala, etc.
• 7-10 years in Data Platform experience- specific to owning and enabling capabilities within an enterprise data ecosystem, including Data Management practices (Analytics/Platform)
• 5+ years' experience with the Azure data & analytics stack: Databricks, Data Factory, SQL DW, Cosmos DB, Power BI, Power Apps, AKS, etc.
• 4+ years of experience in AI, ML, or data science roles
• 3+ years of experience developing Insightful Reports and Dashboard using prominent BI tools like Power BI, Tableau
• Experience with delivering Transformed & Curated Data to Data Science
• Fully conversant with big-data processing approaches and "schema-on-read" methodologies. Preference for a deep understanding of Spark, Databricks, and Delta Lake and applying them to solve data science and machine learning business problems.
• Experience with Agile delivery frameworks and tools: SAFe, Jira, Confluence, Azure DevOps, etc.
• Experience with visualization tools and their application: developing reports, dashboards, and KPI scorecards.
• Familiar deploying enterprise analytics solutions at scale with applicable services: administration, qualification and user access provisioning.
• Experience articulating the business value of analytics projects and progressing solutions from MVP to scaled-up production solutions.
• Ability to work in close partnership with groups across the IT organization (security, compliance, infrastructure, etc.) and business stakeholders in the commercial organizations.
• Ability to develop and maintain productive working relationships with suppliers and specialist technology providers to assemble and maintain a distinctive and flexible mix of capabilities against future requirements.
• The ideal candidate possesses excellent communication skills and the ability to communicate inherently complicated technical concepts to non-technical stakeholders of all levels.

Inclusion at GSK:

As an employer committed to Inclusion, we encourage you to reach out if you need any adjustments during the recruitment process. Please contact our Recruitment Team at IN.recruitment- to discuss your needs.

Why GSK?

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

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we're committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

Inclusion at GSK:

As an employer committed to Inclusion, we encourage you to reach out if you need any adjustments during the recruitment process.

Please contact our Recruitment Team at IN.recruitment- to discuss your needs.

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