Data & Analytics Specialist

Data & Analytics Specialist Education Bachelor’s or Master’s degree in Computer Science, Engineering, Physics, Mathematics, Statistics, or a related field. Expertise / Experience Required Strong proficiency in database management and data engineering. Advanced skills in computer programming. Expertise in developing and maintaining dashboards using data visualization tools. Experience in conducting analysis, developing studies, and employing data mining techniques. Technical Skills Proficiency in Microsoft Office Suite, especially Excel. Advanced knowledge of SQL and database querying. Proficiency in Python for data analysis and scripting. Experience with Data Visualization Tools (Power BI or Tableau). Familiarity with AWS Cloud Services and tools for data handling and processing. Desirable Skills Ability to create compelling stories and presentations from data findings. Experience in digital analytics and social media data analysis. Understanding of statistics and statistical modeling techniques. Personal Attributes Strong data engineering and programming background. Ability to approach data challenges holistically and analytically. Fluent in English, with excellent communication skills. Effective in teamwork and collaboration, including with cross‑functional teams. Proactive problem‑solving skills with a focus on business improvement. Business acumen to balance technical and business perspectives. Strong interpersonal skills with the ability to engage effectively with various stakeholders. Main Roles and Responsibilities Data Lake Project Identify and integrate new data sources, KPIs, and segments to enhance business value. Ensure data integrity and quality through rigorous data cleansing and validation. Collaborate with IT development teams for new data source implementation. Manage information security and compliance with data protection laws. Dashboard Development and Maintenance Design and build dashboards to monitor business performance and generate actionable insights. Maintain and update dashboards and datamarts for ongoing relevance and accuracy. Continuous improvement of data engineering processes to enhance quality and productivity. Data Enrichment and Analysis Explore and test new data sources for potential enrichment. Conduct analysis for customer engagement and monetization campaigns. Undertake digital analytics, including website/app navigation and social media behavior analysis. Strategic KPI and Segment Planning Develop meaningful KPIs and customer segments for business insights. Conduct studies to attract new customers and understand existing customer preferences, demands, and challenges. Collaborate on projects to increase engagement and monetization for strategic partners. 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