Job Description: 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.