Design, develop, and maintain efficient, scalable, and well-documented data pipelines to extract, transform, and load data from various sources., including external data, CRM, supply chain systems, third-party platforms, e-commerce platforms (via APIs), and omnichannel engagement platforms into a centralized data warehouse and on-premise systems.
Build reliable end data model products based on the analysis and reporting requirements for in-market sales data for various markets.
Assist in daily monitoring of ELT pipelines for external sales , CRM and E-commerce, including troubleshooting, and root cause analysis of data pipeline failures to ensure data reliability and uptime.
Data Analytics and Insights
Support the maintenance of data products for our BI Dashboards. (Including third party Market Intelligence data such as IQVIA.
Contribute to the data exploration, extraction, analysis , cleansing, and basic transformation of sales-related data using analytical tools.
Assist in preparing secondary reports, primarily focused on sales performance and market share.
Support and contribute to the ongoing maintenance of business intelligence data visualizations and dashboards to ensure data accuracy.
Provide dedicated support for IQVIA quarterly reporting by assisting with sales data preparation and report generation under guidance.
Contribute to basic interpretation of sales performance data to support business insights under supervision.
Driving Data Culture
Assist in preparing materials and logistics for training sessions on internal dashboards.
Support Unit Testing, System Testing, and User Acceptance Testing (UAT) activities for our Data and Analytics applications, including documentation.
Perform other ad-hoc tasks as and when assigned by the Senior Regional Data & AI Engineer.
KEY REQUIREMENTS:
Currently pursuing a Bachelor's degree in Business Analytics, Data and Analytics, Data Science, Statistics, Mathematics, or a related field.
Previous internship experience with pharmaceutical industry data and regulations is a plus.
Strong proficiency in SQL and data warehousing concepts for both cloud and on-premise platforms. Strong interest in data engineering, data analysis and data visualization
Good analytical skills and proficiency in spreadsheets (e.g., Google Sheets or Microsoft Excel)
Experience with programming languages (e.g., Python, R) for data manipulation and analysis.
Understanding of cloud-based data platforms (e.g., AWS, GCP, Azure) and on-premise data infrastructure.
Basic understanding of market analytics, sales data, and competitive intelligence concepts.
Exceptional communication skills (written and verbal) with the ability to clearly translate complex technical concepts and data insights for non-technical business stakeholders, influencing decisions and managing expectations effectively.
Strong analytical, diagnostic, and proactive problem-solving skills with a proven ability to identify root causes and implement sustainable solutions independently.
Proven ability to manage multiple, diverse data projects concurrently, prioritizing effectively and delivering results in a dynamic environment.
Meticulous attention to detail and a strong commitment to data accuracy and code quality, with a proven track record of implementing robust validation and testing procedures.
Adaptability to a fast-paced environment
Strong time management and organizational skills
Ability to work effectively both independently and as part of a team
Cultural sensitivity and ability to work cross-functionally
Able to process datasets in mandarin language, and to interact and work closely with Chinese markets