Data Modelling: Understanding dimensional modelling (star schema, snowflake schema), data warehousing concepts (ETL/ELT processes), and data modelilng tools.
Database Management: Proficiency in SQL, including advanced querying, data manipulation, and performance tuning. Familiarity with databases like SQL Server, Oracle, MySQL, PostgreSQL, or cloud-based databases (AWS Redshift, Azure SQL/Fabric, Google BigQuery).
Reporting & Visualization: Expertise in BI tools such as Power BI, Tableau, Qlik Sense, or MicroStrategy for creating interactive dashboards, reports, and visualizations.
Data Analysis: Strong analytical and problem-solving skills, including the ability to analyze data trends, identify patterns, and draw meaningful and actionable insights.
Cloud Platforms: Familiarity with cloud platforms like AWS, Azure, or Google Cloud, including their data warehousing and analytics services.
Business Acumen: Understanding and willing to learn of Ergomed business processes, key performance indicators (KPIs), and how data can be used to drive business decisions.
Communication & Collaboration: Excellent communication and interpersonal skills to effectively collaborate with business stakeholders, gather requirements, and present findings.
Problem-Solving: Ability to identify and solve complex business problems using data-driven approaches.
Domain Knowledge: Knowledge of specific industry domains (e.g. clinical trials, pharmacovigilance, healthcare) can be a significant advantage.
Understanding of best practices in master data management, data governance, data literacy principles is an advantage.
Proficiency in scripting languages like Python (with libraries like Pandas, NumPy, and Scikit-learn) for data manipulation, analysis, and automation is an advantage.