Senior Finance Data Analyst

1. Data Collection & Integration

• Collect, consolidate, and manage business and operational data from multiple sources, including ERP systems, databases, and external datasets.

• Design and maintain structured datasets to support management reporting and business analytics.

• Coordinate with different departments to ensure timely and accurate data submission.

2. Data Cleaning & Data Quality Management

• Perform data cleaning, validation, and transformation to ensure accuracy, consistency, and reliability of datasets.

• Identify data inconsistencies and implement data quality controls to improve data integrity.

3. MIS Development & Management

• Develop and maintain Management Information System (MIS) reports for management and business units.

• Prepare recurring management reports, operational dashboards, and performance tracking reports.

• Automate data processing and reporting workflows where possible to improve efficiency.

4. Enterprise Data Warehouse (EDW) Support

• Support the development and maintenance of the Enterprise Data Warehouse (EDW).

• Design data structures, data pipelines, and data models to ensure scalability and usability of the data warehouse.

• Collaborate with IT and data engineering teams to optimize data architecture and accessibility.

5. Data Analysis & Business Insights

• Analyze operational and financial data to identify trends, performance drivers, and business insights.

• Support management and business teams with ad-hoc analysis and data-driven decision support.

• Develop visualization dashboards using BI tools to communicate insights clearly.

6. Data Automation & AI Utilization

• Apply automation tools and AI-assisted analytics to enhance data processing and analytical capabilities.

• Utilize modern data analytics tools to improve reporting efficiency and analytical depth.

• Explore new technologies in data analytics and AI to enhance the organization’s data capabilities.

Education

• Bachelor’s or Master’s Degree in Data Analytics, Computer Science, Information Systems, Statistics, Finance, Business Analytics, or a related field.

Experience

• At least 2–4 years of experience in Data Analytics, MIS, Business Intelligence, or a related discipline.

• Proven experience handling large-scale datasets and integrating multi-source data.

Technical Skills

• Proficiency in SQL and database management.

• Hands-on experience in Data Cleaning, Transformation, and ETL processes.

• Strong understanding of Enterprise Data Warehouse (EDW) concepts.

• Proficiency in Business Intelligence (BI) tools such as Power BI, Tableau, or similar platforms.

• Advanced Microsoft Excel skills, including Power Query and Power Pivot.

Data & AI Literacy

• Solid understanding of Data Analytics and AI-assisted analytics tools.

• Ability to utilize automation or AI tools to optimize data analysis and reporting workflows.

Behavioral Competencies

• Strong analytical thinking and problem-solving skills.

• High attention to detail with a focus on data accuracy.

• Excellent stakeholder management skills, with the ability to bridge the gap between business and technical teams.

• High level of accountability and ownership.

• Proactive learner with a passion for staying current with new data technologies and tools.