Data Analyst Director

is responsible for developing a clear and inspiring vision for the analytics department, outlining its role in achieving the company's long-term strategic objectives, and executing it via a comprehensive analytics strategy, ensuring that data-driven insights contribute directly to business growth and profitability.

This high-level leadership role must provide clear direction and guidance; set expectations for performance and professional development, encourage innovation and creativity, empower the team to explore new methodologies and approaches, effectively delegate tasks, prioritize projects, and allocate resources to maximize team efficiency and productivity.

Additionally, the role must build strong cross-functional relationships, working collaboratively with other department heads to align analytics initiatives with broader company goals.

Responsibilities

• Leadership: lead and mentor a team of data analysts and functional specialists, fostering a culture of collaboration, growth, and innovation within the department.
• Data Analysis: implement advanced analytics techniques to extract actionable insights from large datasets, enabling us to make informed decisions and optimize our lead generation strategies.
• Reporting and Visualization: develop, maintain, improve, and communicate via data visualizations with various stakeholders, translating complex data into easily digestible insights that drive business decisions.
• Database Management: oversee database management activities; create and maintain data pipelines; ensure data accuracy, consistency, and security across all systems.
• Data Storage: manage data storage solutions, making sure that data is stored efficiently and is easily accessible to the analytics team.
• Collaboration: collaborate with cross-functional teams to identify opportunities for using data to drive innovation, optimize processes, and enhance customer experiences.
• Department evolution: define a roadmap for the evolution of analytics capabilities, considering emerging technologies, industry trends, and routine business needs.
• Continuous learning: Develop and implement professional development plans for the whole team.
• Process improvement: automate processes; measure the effectiveness of analytics initiatives, regularly review and refine them as needed
  
  

Requirements:

Experience/Skills:

• 10+ years of experience in data analysis, reporting, and visualization or related fields
• Proficiency in Python (preferable) or R
• Proficiency in data management and database technologies (e.g., SQL, NoSQL databases) for extracting, transforming, and loading (ETL) data
• Understanding of column-oriented databases such as Google Big Query and related ecosystems for handling and analyzing large datasets.
• Knowledge of Google Cloud Storage and other storage solutions for managing structured and unstructured data
• Knowledge of data lifecycle management on Google Cloud
• Direct experience in Power BI / Tableau, or other data visualization tools
• Proficiency in statistical analysis methods, data modeling, hypothesis testing, and AB testing
• Track record of managing multi-functional teams
• Fluent in English
  
  

Education:

• University degree in Data Analytics, Data Science, Computer Science, Mathematics, Statistics, Finance, Economics, or a related field.
  
  

Personal Characteristics:

• Compassionate leader
• Effective communicator
• Flexible and accepting of continuous change
• Highly curious
• Comfortable in a multi-language, multi-cultural environment
• Strong interest in continuous learning
• Strong focus on data-driven decision-making