Data Analyst & AI

We are seeking a highly technical and business-savvy Data Analyst to lead the design and implementation of end-to-end analytical ecosystem. You are a capable and reliable professional who independently manages core analytical tasks while effectively engaging with stakeholders. You possess a solid foundation of technical and interpersonal skills gained through several years of practical experience. You will be responsible for leading the product, translating complex business needs into analytical solutions, and ensuring the delivery of high-quality, scalable data products.

• Bachelor s or Master s degree in computer science, Engineering or a related field of study
• 5+ years strong experience with visualization tools (e.g. Power BI, Qliksense) including advanced features.
• 3+ year s Data Engineering Competency in Google Cloud and ability to apply best practices for security and efficiency in cloud data usage.
• Strong experience of query optimization, data cleaning, and version control (e.g., Git) contributions
• Expert-level proficiency in SQL (BigQuery preferred) and Python
• Proven ability to work as an independent team member on analytical projects from inception to delivery.
• Effective communication of data, analysis, and insights, with the ability to present findings clearly to various audiences.
• Experience in CI/CD pipelines using GitHub, Terraform, and Tekton is a plus

• End-to-End Development: Design and build complex reports and dashboards using Power BI or Qlik Sense, ensuring they are performant, accurate, and meet stakeholder requirements.
• Data Manipulation: Proficiently use SQL preferably Big Query for data analysis, cleaning, and optimization.
• Modeling Visualization: Create visual models (process flows, data flow diagrams) to explain complex concepts and define/calculate key business metrics accurately.
• Cloud Operations: Use Terraform to provision and manage GCP resources, configure cloud data resources for cost-effective operation and implement data transformation pipelines using DataForm or Apache Airflow.
• Requirements Gathering: Lead effective meetings, workshops, and requirements-gathering sessions to understand business needs.
• Analytic Quality: Implement robust data validation and error handling in scripts and pipelines. Consistently deliver high-quality insights and comprehensive data validation.
• Peer Review: Contribute to analytical work reviews (reviewing queries and dashboard designs) and provide constructive feedback to team members.
• Documentation: Produce clear documentation for analytical processes, data sources, and key definitions. Create technical design documents for analytical solutions and data models.
• Process Optimization: Propose improvements to existing reports and processes with AI or other emerging technologies.
• Scalability: Design analytical solutions with scalability in mind to handle growing data volumes.