Data Analyst - Python/Business Intelligence (3-10 yrs)

Role and Profile : Data Analyst

Job description

- Analytics with predominant experience in SQL, SAS, Statistics, R , Python, Visualization

- Experienced in writing complex SQL select queries (window functions & CTEs) with advanced SQL experience.

- Should be an individual contributor for initial few months based on project movement team will be aligned.

- Strong in querying logic and data interpretation Solid communication and articulation skills

- Able to handle stakeholders independently with less interventions of reporting manager

- Develop strategies to solve problems in logical yet creative ways.

- Create custom reports and presentations accompanied by strong data visualization and storytelling.

- We would be excited if you have.

- Excellent communication and interpersonal skills

- Ability to meet deadlines and manage project delivery

- Excellent report-writing and presentation skills Critical thinking

- Ensure high quality BI solution deliveries.

- Server Performance, capacity, utilization monitoring and Health monitoring Optimization and Performance tuning of QlikSense & Qlikview applications

- Define best practices for QlikSense & Qlikview deployment and create reusable templates

- Perform detailed analysis of source systems and source system data and model that data in Qlik.

- Hands on experience with Qlik sense Extensions (Javascript/Angular)

- Advanced knowledge using set analysis & variables.

- Data Cleaning and Preparation: Rigorously inspecting and cleansing data to ensure its quality and accuracy. This involves identifying and correcting errors, filling missing values, and standardizing data formats.

- Data Integration and Warehousing: Efficiently combining data from different sources to create a unified and coherent dataset. Managing data storage and retrieval in data warehouses.

- Data Quality Assurance: Continuously monitoring and ensuring the high quality of data. Implementing processes and standards to maintain data integrity.

- Data Analysis and Interpretation: Developing a deep understanding of data attributes. Applying analytical skills to interpret, analyze, and derive meaningful insights from data.

- Reporting and Visualization: Creating reports and dashboards to present data insights in a clear, understandable manner. Utilizing data visualization tools to aid in understanding complex data patterns.

- Collaboration and Communication: Working with various teams to understand data needs, share insights, and support decision-making processes.