SUMMARY OF THE ROLE

As Data Excellence Manager in SFE department, You will master pharma commercial business scenarios including field sales execution, customer coverage, hospital & retail channel operation, marketing campaign performance, and sales KPI system. Based on in-depth business understanding, you will unify commercial KPI calculation logic, business statistical standards and multi-dimensional business definition standards, build professional pharmaceutical commercial KPI logic library, and embed standardized rules into enterprise business glossary to eliminate cross-team business metric divergence caused by different commercial interpretation.

You apply hands-on data processing skills via Power Query (Excel/Power BI) to perform data profiling, cleansing tasks, and maintain consistent, high-quality data across all BI and AI reports.

ROLE & RESPONSIBILITIES

1. Cross-Functional Liaison for Data Alignment and Central Reporting

• Act as the dedicated communication liaison across SFE team, MI teams, Digital team and IT team to unify the presentation standards of data from cross-functional teams within enterprise central reports.
• Align unified statistical calibers, calculation logic and dimension definitions for all core KPIs used in central dashboards and standardized reports; eliminate inconsistent metrics caused by divergent business interpretation.
• Document formal KPI logic libraries, standard calculation formulas and business interpretation rules, embed them into the enterprise business glossary and data dictionary for global reference.

2. Data Quality & Integrity Management (With Hands-On Data Processing)

• Conduct hands-on data profiling, cleansing and anomaly identification using Power Query (Excel/Power BI) to extract, transform and load business datasets
• Ensure data consistency and data quality across all types of BI reports/AI tools and reports.

3. Leverage Generative AI, Large Language Models (LLMs) and AI Agents to Optimize Data Management & Reporting Workflows

• Design and deploy AI agent-assisted automation tools to accelerate business glossary compilation, data dictionary maintenance, critical data element extraction and cross-department KPI standard alignment for MI and behavioral reports.

REQUIREMENTS

Essential Qualifications & Experience

1. Bachelor’s degree in Information Management, Data Science, Computer Science, Pharmacy, Life Sciences, Business Administration or equivalent professional experience; Master’s degree preferred.

2. Minimum 6 years progressive hands-on experience in pharmaceutical/biotech industry, with core experience in commercial data management, SFE data governance, sales & marketing business data analysis or commercial MI reporting; familiar with pharmaceutical industry commercial operation model, medical representative sales scenario, hospital/channel business logic and industry compliance requirements.

3. Practical expertise in metadata management, data lineage, business glossary, critical data element definition and master data harmonization.

4. Strong hands-on data processing capability: Advanced proficiency in Power Query (Excel & Power BI) for data extraction, transformation, merging, deduplication, profiling and building repeatable data cleansing logic; able to independently process large unstructured raw business datasets and deliver standardized clean data assets.

Preferred Qualifications

1. Completed practice or project cases of deploying enterprise AI Agents, generative AI tools (Copilot, Azure OpenAI etc.) within data governance, MI reporting or data stewardship scenarios.

2. Hands-on experience building LLM-aided business glossary, data dictionary and KPI logic standardization tools

Date Posted

21-7月-2026

Closing Date

29-9月-2026

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.