Senior Data Analytics and Visualization Engineer Responsibilities Advanced Dashboard & Report Development: Design, develop, and deploy highly performant, visually compelling, and intuitive enterprise dashboards and reports (with a primary focus on Power BI, Tableau, or Qlik) Requirement Gathering & Stakeholder Management: Actively liaise with Product Owners, business analysts, and corporate client stakeholders. Conduct detailed analysis of business problems, gather requirements, and facilitate interactive demo sessions Data Modeling & Profiling: Engineer and implement optimal data models (including Dimensional Modeling, Star, and Snowflake schemas). Conduct thorough data preparation, profiling, and quality validation Python Integration & Process Automation: Utilize Python (Pandas, NumPy, and related libraries) to automate data processes, perform advanced statistical profiling, or integrate custom predictive analytics and data science models directly into visual BI dashboards Environment Administration & Security: Oversee and manage the reporting environments and workspaces. Define and implement robust security frameworks, including Row-Level Security (RLS) and access governance Modern Data Architecture Collaboration: Contribute to high-level architecture discussions. Align BI deliverables with modern data structures (Data Warehouses, Data Lakes, Lakehouses/Delta Lakes, and Datamarts) and staging processes QA & Testing Standards: Design and contribute to comprehensive testing methodologies for data products to ensure 100% accuracy, speed, and alignment with industry standards Agile & DevOps Principles: Work actively within a modern Agile development environment (SCRUM/Kanban) and champion the adoption of CI/CD principles and BI version control practices Requirements Professional Experience: 5+ years of hands-on experience developing, designing, and maintaining complex BI solutions using tools like Power BI (strongly preferred), Tableau, or Qlik Programming & Scripting: Strong programming proficiency in Python and advanced SQL (including DAX or MDX) Database Expertise: Proven background in relational databases (such as MS SQL Server, Oracle, MySQL, and PostgreSQL). Experience with high-performance columnar analytical databases (e.g., ClickHouse) is highly valued Data Engineering Concepts: Clear understanding of data tiering (landing, staging area, data cleansing, profiling, and security) and data warehouse architecture (DWH, Data Lake, Delta Lake, Datamarts) Cloud Architecture: Hands-on flexibility using Cloud platforms (specifically AWS-including services like S3, Glue, Athena, and Lambda-or equivalent services in Azure, GCP, or Snowflake) Quality Assurance: Demonstrated expertise in testing data products, validation, and dashboard performance tuning Agile Frameworks: Experience working in fast-paced Agile development environments (SCRUM, Kanban) CI/CD & DevOps: Familiarity with modern CI/CD principles and version control tools for report deployment Communication & English Skills: Strong presentation and communication skills, with a proven capability of bridging technical data concepts to C-level executives. Fluent English proficiency (Upper-Intermediate level or higher) Nice to have ETL/ELT Pipeline Development: Experience building, monitoring, and optimizing ETL data pipelines Low-Code/No-Code Apps: Familiarity with low-code application development platforms (such as Power Apps) Advanced BI Certifications: Professional certifications, such as Microsoft Certified: Power BI Data Analyst Associate, Power Platform App Maker, or cloud certifications