HR Data Solutions Specialist

Job Title: HR Data Solutions Specialist GCL: D3 Introduction to role: Are you ready to turn governed HR data into decisions that shape a high-performing, patient-focused enterprise? This role is your opportunity to deliver trusted, secure and actionable workforce data that leaders rely on to make informed choices about how we attract, develop and support our people. Can you translate complex workforce data into clear, reusable data products that are easy to access and simple to trust? You will work at the intersection of HR, Reporting & Analytics, IT and external partners to engineer data pipelines, strengthen controls and elevate data quality so that insights are reliable and timely. Your impact will span day-to-day continuous improvement and strategic events such as Mergers and Acquisitions. By improving data quality, access governance and AI stewardship, you will help ensure we use employee data responsibly, accelerate transformation and ultimately support the delivery of life-changing medicines. Accountabilities: Data Product Analysis and Insight: Analyze HR Data Products and workforce data to identify trends, anomalies, data-quality issues and opportunities for improvement, turning findings into prioritized actions that elevate decision-making. Data Stewardship and Domain Expertise: Act as a domain expert for defined HR data areas, maintaining data definitions, business rules, relationships, ownership, metadata and lineage to ensure transparency and appropriate use. Requirements and Planning: Gather and document data requirements, business rules, user needs, acceptance criteria and expected outcomes; support planning, prioritization, testing, release and collaborator communications to deliver the right solutions at the right time. Data Engineering and Pipelines: Develop, test, maintain and improve data pipelines and solutions in line with standards; perform data cleansing, transformation, mapping, validation and reconciliation to ensure robustness and reusability. Data Quality Management: Identify data-quality issues, investigate root causes and coordinate corrective actions; apply data testing, reconciliation, documentation and control practices to sustain high data standards. Access Governance and Security: Support access governance for confidential and sensitive HR data, aligning with policies and controls; reinforce role-based access and least-privilege principles to protect privacy and ensure compliance. Reporting and Insights Delivery: Support the delivery of workforce reports, dashboards and insights using approved enterprise technologies, ensuring outputs are accurate, timely and aligned to collaborator needs. Mergers, Acquisitions and Change: Prepare and validate HR data for M&A, system changes and interpersonal initiatives; complete data loads using approved templates, perform pre- and post-load checks, and investigate exceptions, advancing when appropriate. AI Governance and Responsible Use: Give to AI governance activities, ensuring appropriate data use, access, privacy, risk management and human oversight across analytics involving employee data. Ways of Working and Teamwork: Partner with HR, People Services, Reporting & Analytics, IT, vendors and business collaborators; work through structured requirements, backlogs and Agile methods; promote data-driven decision-making, open communication and continuous improvement. Essential Skills/Experience: Bachelor’s degree or equivalent experience in Data Analytics, Data Management, Information Technology, Computer Science, Engineering, Statistics, or related field. Demonstrable experience in data analysis, data management, reporting, data governance, data engineering, HR technology, or related fields. Strong passion for data and a genuine interest in using data to improve business performance and workforce decisions. Experience with data cleansing, transformation, mapping, validation, reconciliation, and data-quality assessment. Ability to analyze complex data sets, identify patterns and anomalies, investigate issues, and communicate findings clearly. Understanding data governance principles, including data ownership, data quality, access, privacy, metadata, and proper use of sensitive data. Experience chipping in to reports, dashboards, data products, or analytical solutions. Advanced spreadsheet capability, including data manipulation, formulas, lookups, pivot tables, and validation techniques. Understanding data models, relationships, definitions, business rules, and data flows. Understanding data pipelines and the data lifecycle, including ingestion, storage, transformation, preparation, and presentation. Ability to apply data testing, reconciliation, and quality assurance practices. Experience with, or proven interest in, automation, scripting, or programming for data analysis and process improvement. Understanding access governance concepts, including role-based access and least-privilege principles. Ability to work with structured requirements, defined work packages, backlogs, or Agile delivery methods. Strong customer orientation, communication skills, attention to detail, and logical problem-solving ability. Ability to work independently and cross-functionally across a global, matrixed and cross-cultural organization. Proven initiative, accountability, learning agility, and willingness to develop new technical and HR data skills. Desirable Skills/Experience: Knowledge of HR data, workforce processes, or HR technology. Experience with HR functionality, data management, and business processes. Experience supporting HR data migration, system implementation, organizational change, Mergers and Acquisitions or workforce data integration. Experience with data visualization, business intelligence, or enterprise reporting technologies. Experience with SQL, Python, VBA, PowerShell or similar technologies. Exposure to cloud data platforms, data warehouses, lake houses, orchestration tools or enterprise data platforms. Experience developing, testing, deploying, or maintaining data pipelines and data applications. Exposure to DevOps or DataOps practices, including source control, automated testing, deployment automation, monitoring or release management. Experience using data catalogues, metadata repositories, business glossaries or lineage tools. Understanding data and application design patterns, APIs, integration patterns, or scalable data solutions. Experience supporting data access reviews, data stewardship, data-quality frameworks, or broader data-governance initiatives. Experience with AI governance, responsible AI, model governance or analytics involving employee data. Knowledge of data privacy principles, including privacy by design, data minimization, retention, and purpose limitation.</