SQL (Advanced level - complex queries, optimization, database design)

Python or R for data analysis and statistical computing

Data Visualization Tools (Tableau, Power BI, Looker, or Google Data Studio)

Excel (Advanced - pivot tables, VLOOKUP, data modeling)

Database Management (MySQL, PostgreSQL, or similar relational databases)

ETL Tools and Data Pipeline Development

Statistical Analysis and Hypothesis Testing

Data Warehousing concepts and architecture

Basic understanding of APIs and data integration

Version Control Systems (Git/GitHub)

Strong analytical and critical thinking abilities

Excellent communication and presentation skills

Ability to translate business requirements into technical specifications

Collaborative mindset with strong teamwork capabilities

Problem-solving and creative thinking

Attention to detail and data accuracy focus

Time management and ability to handle multiple projects

Curiosity and passion for continuous learning

Stakeholder management and relationship building

Ability to work independently and take ownership of projects