Lead Data Analytics and Visualization Engineer Responsibilities Supervise, mentor, and inspire a team of data analysts and BI engineers. Foster a culture of continuous learning, collaboration, and engineering excellence Partner directly with client Product Owners and C-level stakeholders. Conduct detailed analysis of business problems, gather functional and technical requirements, and deliver interactive demo sessions Establish and enforce standards for visualization design, report performance tuning, query optimization, and technical QA testing across the team Design and build advanced-level dashboards and interactive reports (using Power BI, Tableau, or similar enterprise BI tools) Architect robust, scalable dimensional data models (Star and Snowflake schemas). Design and implement central Data Warehouse (DWH) solutions and clean data marts Build, manage, and optimize automated ETL pipelines. Maintain overall data cleanliness, profiling, and quality workflows (using modern orchestration tools like Apache Airflow) Oversee security setups (e.g., Row-Level Security, workspace governance) and administer the reporting and analytical environments Leverage scripting languages (like Python) to build advanced analytics models, including RFM (Recency, Frequency, Monetary Value), ABC/XYZ analysis, and Customer Lifetime Value (CLV) predictions Design frameworks to monitor complex metrics (such as CPA, ARPU, retention, and user behavior) to drive product performance, detect fraud, and optimize business processes Requirements 5+ years of hands-on experience developing high-performance BI dashboards and data models using tools like Power BI (highly preferred), Tableau, Metabase, or equivalent 1+ years of proven experience leading or mentoring a team of data professionals in an Agile environment Expert-level SQL knowledge, with a deep background in relational databases (MySQL, PostgreSQL, MS SQL Server) and experience with large-scale columnar/cloud data systems (such as ClickHouse or AWS Redshift) Solid understanding of staging areas, data cleansing, profiling, and modern data architecture concepts (DWH, Data Lakes, Lakehouses/Delta Lakes, and Data Marts) Proficiency in Python (specifically Pandas, NumPy, and statistical libraries) for data manipulation, automation, or custom analytical scripts Familiarity with cloud technologies, preferably AWS services (S3, Redshift, Athena, Lambda, Glue) or equivalent Azure, GCP, or Snowflake architectures Practical experience working in an Agile development environment (SCRUM, Kanban), with expertise in testing data products for latency and accuracy Exceptional ability to break down highly complex technical data structures into clear business insights for non-technical audiences Strong English proficiency (Upper-Intermediate level or higher) Nice to have Hands-on experience with orchestration frameworks such as Apache Airflow Strong background in or understanding of corporate financial modeling, KPI setup, budgeting, and auditing procedures Understanding of CI/CD principles and automated deployment frameworks for BI and reporting tools