Digital Marketing Analyst

Responsibilities

• Business Understanding & Strategy: Collaborate closely with Digital Marketing business stakeholders to understand their analytical needs, key performance indicators (KPIs), and strategic objectives. Translate complex business questions into clear, actionable analytical requirements.
• Data Analysis & Insights: Conduct in-depth analysis of media and Digital performance data, identifying trends, patterns, and opportunities for optimization. Provide actionable insights and recommendations to improve media effectiveness and business outcomes.
• Dashboard & Report Development: Design, develop, and maintain interactive dashboards and reports using business intelligence (BI) tools (e.g., Power BI, Qlik Sense) to visualize key metrics and performance trends for various stakeholders.
• Analytical Modeling: Develop and implement analytical models (e.g., forecasting, attribution, segmentation) to address specific business challenges and provide deeper insights into media and Website performance.
• Data Pipeline Development: Build, maintain, and optimize data pipelines to ensure timely, accurate, and reliable data flow from various data sources into our analytical platforms, utilizing programming languages like Python and SQL.
• Process Improvement: Identify opportunities to enhance data collection, processing, and analysis workflows. Proactively suggest and implement improvements to increase efficiency and accuracy within the analytics processes.
• Collaboration & Communication: Work cross-functionally with data engineers, marketing teams, and other business units to ensure data consistency and deliver integrated analytical solutions. Effectively communicate complex analytical findings to non-technical audiences.
  

Qualifications

• Analytical Prowess: Demonstrated strong analytical, problem-solving, and critical thinking skills with the ability to interpret complex data and draw meaningful conclusions.
• Digital Marketing Expertise: Solid understanding of digital marketing concepts, channels (e.g., paid search, social, display, SEO), and metrics (e.g., impressions, clicks, conversions, CPA, customer Journey, Optimisation).
• Business Intelligence Tools: Proven proficiency in designing and developing dashboards and reports using leading BI tools such as Microsoft Power BI and Qlik Sense.
• Programming Languages: Strong command of Python for data manipulation, analysis, and scripting, along with expert-level proficiency in SQL for querying and managing large datasets.
• Cloud Environment: Familiarity and hands-on experience working within the Google Cloud Platform (GCP) environment (e.g., BigQuery, Cloud Storage, Cloud Functions).
• Data Storytelling: Ability to present complex data and insights in a clear, concise, and compelling manner to both technical and non-technical audiences.