Data Analyst

Keyrus is an international consulting firm, specializing in the integration of data intelligence and Digital solutions. With over 4000 employees spread across 27 countries, Keyrus continues to deliver on such projects to a wide range of clients from various industries including but not limited to Banking/Finance, Healthcare/pharmaceuticals, FMCG, Oil & Gas, and more.

As part of Keyrus solution delivery, we are also in a position to recruit and place technical consultants to complement on existing client projects with their expertise. As such, we seek innovative and agile people to support ambitious and forthcoming technological challenges.

About the Role

We are looking for a Data Analyst Consultant to support data-driven decision-making by transforming business data into meaningful insights. The successful candidate will work closely with stakeholders to develop reports, dashboards, and analytical solutions that support business and operational objectives.

Key Responsibilities

• Gather, analyze, and interpret data from multiple sources to identify trends and business insights.
• Develop and maintain dashboards, reports, and visualizations using Power BI or similar BI tools.
• Collaborate with business stakeholders to understand reporting and analytics requirements.
• Perform data validation and quality checks to ensure accuracy and consistency.
• Support ad-hoc analysis and provide actionable recommendations to business teams.
• Work closely with data engineering and technology teams to improve data availability and reporting capabilities.

Requirements

• 2-3 years of experience in Data Analytics, Business Intelligence, or a related field.
• Strong SQL skills and experience querying large datasets.
• Hands-on experience with Power BI
• Proficiency in Excel and data analysis techniques.
• Strong analytical, problem-solving, and communication skills.
• Experience translating business requirements into dashboards and reports.

Nice to Have

• Experience with Python for data analysis and automation.
• Exposure to Databricks, Azure, or cloud-based data platforms.
• Knowledge of data modelling and data warehousing concepts.
• Experience working with financial services, aviation, or asset-intensive industries.