Associate Director- Data Platform and BI Services
GSK is hiring an Associate Director- Data Platform and BI Services. Level rates it ; you can apply on GSK.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions LangChain, LangGraph and Databricks among its tools and skills.
- Level classes it as an executive role.
- GSK has 949 other open roles on Level.
- Posted in the last few days.
AI in this role
Job Purpose:
We are seeking an experienced Associated Director- Data Platform & BI Services to provide technical leadership and service ownership across enterprise Azure Data Platform and Power BI services. This role will lead the delivery, governance, operation, and continuous improvement of Azure, Databricks, Data Lake, data engineering, integration, and Power BI capabilities, ensuring scalable, secure, reliable, and cost-effective services.
The role will oversee platform engineering standards, security and access controls, Power BI services, CI/CD, monitoring, performance, production operations, and service management, while driving automation, Generative AI, Agentic AI, and emerging technology adoption. As technical Product Owner, the Senior Manager will translate business requirements into prioritized platform capabilities and ensure solutions align with GSK-approved design patterns, security, engineering, and governance standards.
Key Responsibilities:
Platform, AI & Technology Leadership:
- Lead enterprise and solution architecture for major commercial data, analytics, AI/ML, and Power BI initiatives.
- Lead technology delivery and platform enablement for major Commercial / Patient Data, Analytics, AI/ML, and Power BI initiatives.
- Drive AI and Agentic AI enablement, including AI agents, MCP servers, enterprise integrations, security, and governance.
- Ensure solutions follow GSK-approved architecture patterns, technology standards, security controls, and governance guidelines.
- Partner with Architecture, Security, Engineering, and Global Tech teams to obtain required technical reviews and approvals.
- Oversee infrastructure provisioning and ensure compliance with established enterprise platform and security standards.
- Drive cross-functional technical alignment and dependency management across US Commercial, Data, MDM, Engineering, Global Tech, and partner teams.
Azure Data Platform & Engineering Leadership:
- Lead and oversee Azure Data Lake Platform services, including Azure Databricks, ADF, ADLS, Unity Catalog, and related Azure capabilities.
- Ensure platform solutions adhere to approved enterprise design patterns, engineering standards, security controls, and GSK technology guidelines.
- Ensure solutions meet scalability, reliability, security, performance, operational support, and cost-efficiency requirements.
- Drive adoption of standardized, reusable, configuration-driven platform capabilities and integration patterns.
- Partner with Architecture and Engineering teams to ensure new solutions align with enterprise technology direction and platform standards.
- Promote consistent implementation practices across Data Lake, analytics, AI/ML, and downstream data services.
Platform Governance & Technical Operations:
- Manage platform user access, roles, permissions, Microsoft Entra ID (Azure AD) groups, service principals, and access approval processes.
- Implement and maintain role-based access controls (RBAC) across Azure, Databricks, Unity Catalog, Power BI, Data Lake, and related platform services.
- Ensure appropriate access controls for data, workspaces, applications, service principals, storage, and platform resources.
- Oversee user onboarding/offboarding, access reviews, segregation of duties, privileged access, and remediation of access-related risks.
- Ensure platform configurations and operational processes comply with GSK security, governance, audit, and approved technical standards.
- Drive platform controls, audit readiness, automation, monitoring, technical risk remediation, and continuous improvement.
Power BI Platform & Service Management:
- Manage Power BI services including capacities, workspaces, gateways, semantic models, dataflows, reports, dashboards, and platform configurations.
- Oversee user access, roles, security groups, RLS, workspace provisioning, sharing, and approval processes.
- Establish technical standards for report development, semantic modeling, workspace management, deployment pipelines, and CI/CD processes.
- Govern the end-to-end report and semantic model lifecycle, including development, testing, deployment, certification, support, and retirement.
- Drive performance optimization, automation, monitoring, security, standardization, and cost-effective utilization of Power BI services.
- Ensure Power BI solutions integrate effectively with Databricks, Azure Data Lake, and enterprise data platforms while following GSK-approved technical, security, and governance standards.
Technical Product Ownership & Requirements Management:
- Lead technical product ownership for Data Platform and Power BI services, including platform roadmap, capabilities, enhancements, and modernization.
- Translate business needs into technical requirements, data flows, integrations, security requirements, platform dependencies, and acceptance criteria.
- Review technical requirements and user stories across Azure, Databricks, Data Lake, APIs, data pipelines, Power BI, and related platform services.
- Assess technical feasibility, dependencies, risks, security, performance, and operational readiness before implementation.
- Manage and prioritize backlog across new capabilities, technical debt, automation, platform enhancements, security remediation, and production support.
- Coordinate end-to-end technical delivery while ensuring alignment with GSK-approved standards, design patterns, security, and governance requirements.
Platform Service Operations & Technical Leadership:
- Lead day-to-day Data Platform and Power BI service operations, ensuring platform availability, reliability, performance, security, and operational readiness.
- Oversee JIRA backlogs, ServiceNow incidents, service requests, problem records, change requests, and operational support queues, ensuring appropriate prioritization and resolution.
- Drive resolution of complex technical issues across Azure, Databricks, Data Lake, data pipelines, integrations, Power BI, gateways, access, and platform services.
- Lead root-cause analysis (RCA), problem management, corrective/preventive actions, technical risk remediation, and recurring-issue elimination.
- Establish and monitor service KPIs, SLAs, platform health, incident trends, capacity/performance metrics, escalation paths, and operational dashboards.
- Coordinate production deployments, change management, release readiness, environment dependencies, and post-production support across engineering and support teams.
- Provide technical direction to Data Engineering, Power BI, platform, and support teams, ensuring consistent engineering, support, and operational practices.
- Partner with Cybersecurity, Data Governance, infrastructure, application, and business teams to resolve cross-platform dependencies, security issues, and production risks.
- Drive automation, monitoring, alerting, operational documentation, support procedures, and continuous service improvement to improve platform stability and supportability.
- Communicate service health, critical incidents, technical risks, dependencies, remediation plans, and platform priorities to leadership and key stakeholders.
Platform Service Operations & Technical Leadership:
- Drive innovation across Data Platform and Power BI services by evaluating and adopting emerging technologies, tools, and engineering capabilities.
- Lead POCs and technical evaluations across Generative AI, Agentic AI, AI-assisted development, data engineering, analytics, and platform automation.
- Identify opportunities to apply AI agents, MCP, RAG, intelligent automation, and AI coding capabilities to improve engineering productivity and platform operations.
- Promote automation across data pipelines, testing, deployment, monitoring, data quality, incident management, and operational support.
- Evaluate new capabilities within Azure, Databricks, Power BI, and the broader data/AI ecosystem for potential enterprise adoption.
- Define measurable success criteria, technical feasibility, scalability, security, cost, and business value for innovation initiatives before production adoption.
- Drive successful POCs toward production-ready, reusable, governed, and scalable enterprise capabilities in alignment with GSK standards.
Required Skills & Qualifications:
- 10+ years of experience in data engineering, data platforms, analytics, BI, or enterprise technology, with significant technical leadership and platform/service ownership responsibilities.
- Strong hands-on knowledge of Microsoft Azure, Azure Databricks, ADLS, ADF, Unity Catalog, and Power BI in enterprise-scale environments.
- Strong understanding of data engineering, data modeling, data integration, APIs, cloud platforms, security, scalability, performance optimization, and cost management.
- Experience managing Power BI services, including capacities, workspaces, gateways, semantic models, reports, security, refresh processes, deployment, performance, and production support.
- Experience with Microsoft Entra ID (Azure AD), RBAC, security groups, service principals, user roles, access approvals, and platform/data access controls.
- Experience applying enterprise-approved design patterns, engineering standards, security controls, governance requirements, and reusable platform capabilities.
- Experience driving Generative AI, Agentic AI, automation, and emerging technology initiatives, including technical evaluations, POCs, enterprise integration, and production enablement.
- Demonstrated experience in technical product/platform ownership, including requirements, roadmaps, backlog prioritization, technical dependencies, delivery readiness, and cross-team execution.
- Experience with JIRA, ServiceNow, Azure DevOps/CI/CD, release management, incident/problem management, RCA, change management, monitoring, and production operations.
- Strong understanding of data governance, data quality, access management, security, and healthcare/pharma data domains.
- Strong technical leadership, communication, and stakeholder-management skills with the ability to coordinate across engineering, security, governance, analytics, infrastructure, support, and business teams.
Preferred Skills:
- Experience with Generative AI and Agentic AI technologies, including multi-agent systems, MCP, RAG, prompt engineering, LLM integration, and Responsible AI practices.
- Hands-on knowledge of modern AI engineering frameworks and tools such as LangGraph, LangChain, LangSmith, vector databases, and AI-assisted development tools.
- Strong understanding of modern data-platform concepts, including data products, data mesh, metadata-driven frameworks, self-service analytics, lakehouse patterns, and open table formats such as Apache Iceberg and Delta Lake.
- Experience with AI/ML platforms, MLOps, model lifecycle management, monitoring, and production AI solutions.
- Strong understanding of Power BI semantic models, DAX, data modeling, gateways, capacity/performance optimization, deployment pipelines, and enterprise BI governance.
- Knowledge of healthcare, patient, commercial, marketing, and real-world data domains, with an understanding of data privacy, quality, security, and governance considerations.
- Experience driving automation and reusable engineering capabilities across ingestion, data quality, testing, CI/CD, monitoring, operational support, and platform management.
- Ability to evaluate emerging capabilities across Azure, Databricks, Power BI, data engineering, and AI ecosystems and transition successful POCs into scalable, governed production solutions.
- Demonstrated technical leadership in driving engineering standards, reusable patterns, platform modernization, innovation, and cross-functional technology adoption.
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Skills
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-adjustments@gsk.com to discuss your needs.
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How we rate this
Associate Director- Data Platform and BI Services at GSK rates 71 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How have you integrated a large language model into a production application?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you monitor a model once it's live, and how do you know it needs retraining?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, LLM Integration, AI agents, and ML Ops. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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