Lenovo

The WW Data Analyst/ Operations BI Developer will play a pivotal role in designing, developing, implementing, and delivering Business Intelligence (BI) solutions to drive informed decision-making across the organization. This role involves close collaboration with both business and IT teams to identify key requirements and transform raw data into actionable insights. The ideal candidate will have a strong background in SQL, hands-on experience with various database environments (both on-premises and cloud), and expertise in dimensional modeling.

Responsibilities

• Analyze, transform, and structure raw data from diverse sources to create well-organized, accurate, and highly efficient datasets tailored for reporting and analytical purposes.
• Develop, maintain, and optimize datasets to improve data quality, streamline processing, and enhance performance for BI and reporting solutions.
• Collaborate on BI development projects, focusing on back-end structures and front-end visualizations, using tools like PowerBI and Qlik to create compelling, user-friendly dashboards and reports.
• Partner closely with internal stakeholders, such as reporting and analytics teams, to understand business needs, translate them into data requirements, and deliver BI solutions that meet those needs.
• Work in close alignment with IT and Digital Transformation teams to implement technical solutions that support data integration, data warehousing, and analytics across the organization.
• Lead data profiling and data cleaning efforts to ensure the highest data integrity standards.
• Actively contribute to the organization's data governance by establishing and adhering to best practices in data management, security, and compliance.

Qualifications

• Advanced SQL knowledge with proven experience working with relational databases and query authoring. Familiarity with a variety of SQL databases is essential.
• Strong interpersonal, communication, and collaboration skills with fluency in spoken and written English, enabling effective work with global teams.
• Solid understanding of data warehousing principles, including ETL/ELT processes, STAR and snowflake schemas, and familiarity with Kimball and Inmon methodologies.
• Proficiency in Python for data integration, data manipulation, and building data pipelines; experience with scheduling tools like AirFlow is a plus.
• Hands-on experience with BI tools (e.g., Qlik, PowerBI) for visualization and dashboard creation is highly preferred.
• A degree in Computer Science, IT, or a similar field; a Master’s degree is advantageous.
• Relevant data engineering certifications (e.g., Databricks Certified Data Engineer) are a plus.