Data Analyst

Job Title:

Location:

Experience

Role Purpose

Data Analyst

Key Accountabilities

• Data Wrangling
• Manage and integrate large, structured datasets from multiple internal and external sources.
• Apply SQL and data transformation techniques to clean, join, and prepare data for analysis.
• Descriptive & Diagnostic Analytics
• Analyse complex datasets to identify key trends, patterns, and insights.
• Develop prescriptive and diagnostic analytics to support data-driven decision-making.
• Data Visualization & Reporting
• Design and automate dashboards, visualizations, and interactive reports using BI tools such as Power BI, Tableau, or Qlik.
• Present findings clearly to both technical and non-technical stakeholders through compelling data storytelling.
• Coding & Scripting
• Write, test, and maintain scripts in SQL, Python, or R to extract, transform, and analyse data efficiently.
• Build automation scripts for recurring data processing and reporting workflows.
• Data Modelling
• Develop and maintain data models ensuring data integrity, scalability, and reliability for advanced analytics use cases.
• Data Quality & Validation
• Create and execute data validation and reconciliation checks to ensure accuracy and completeness.
• Implement measures to enhance data governance and data reliability.
• Risk & Issue Management / Agile Ways of Working
• Identify and mitigate data-related risks while ensuring compliance with data security and privacy principles.
• Collaborate within Agile teams, contribute to sprint planning, retrospectives, and process improvement.
• Domain Knowledge & Collaboration
• Apply business domain knowledge to contextualize data findings.
• Partner with Business Analysts, Engineers, and Product Teams to align analytical solutions with business objectives.
• Soft Skills
• Demonstrate strong problem-solving, communication, collaboration, critical thinking, and data storytelling skills in daily tasks.
  

Required Skills & Competencies

• Strong proficiency in SQL for querying and transforming large datasets.
• Hands-on experience with data visualization tools (Power BI, Tableau, or equivalent).
• Experience with Python or R for analytics and automation.
• Knowledge of data modelling and ETL/ELT processes.
• Strong understanding of data governance, validation, and quality assurance principles.
• Analytical mindset with attention to detail and problem-solving ability.
• Excellent communication and stakeholder management skills.
  

Good To Have Skills

• Experience with cloud platforms such as AWS, GCP, or Azure.
• Familiarity with DBT, Snowflake, or other modern data stack tools.
• Exposure to machine learning, predictive analytics, or AI-driven insights.
• Certification in Data Analytics, Power BI, or SQL.
• Knowledge of Agile methodologies and experience working in cross-functional squads.