Job Summary:
We are seeking a motivated and detail-oriented Data Analyst to support our Enterprise Data Platform (EDP) initiative. The successful candidate will play a key role in analyzing, documenting, and enhancing enterprise data assets, working closely with data engineers, architects, and business stakeholders to ensure data is accurate, accessible, and aligned with strategic goals. This role emphasizes hands-on data analysis, integration, and platform enhancement, with a strong focus on leveraging modern data technologies and analytical methodologies.
Key Responsibilities:
Data Analysis & Documentation
- Analyze data sources, structures, and flows to support the integration and standardization of data within the EDP.
- Document metadata, data definitions, and business rules to build and maintain a centralized data catalog.
- Conduct data profiling and quality assessments to identify inconsistencies, redundancies, or gaps.
Reporting & Insights
- Develop dashboards, reports, and visualizations to monitor data health, usage, and compliance.
- Provide actionable insights to improve data lineage tracking and access controls.
Cross-functional Collaboration
- Partner with IT, data governance teams, and business units to understand data needs and translate them into platform requirements.
- Support data modeling and schema design discussions with data platform teams.
Continuous Improvement
- Identify opportunities to enhance data usability, performance, and integrity across the EDP.
- Participate in data maturity assessments and roadmap planning.
Qualifications:
Required:
- Bachelor’s degree in Computer Science, Information Systems, Mathematics, Statistics, or a related field.
- 2–3 years of experience in data analysis, preferably in financial services or enterprise environments.
- Proficiency in SQL and experience with relational databases or data warehouses.
- Familiarity with data modeling and ETL processes.
- Strong analytical and problem-solving skills with attention to detail.
- Experience with data visualization tools.
- Passionate in Data.
Preferred:
- Experience with machine learning and AI-powered data management techniques.
- Experience with cloud data platforms.
- Knowledge of data cataloging tools.
- Exposure to enterprise data management initiatives or data lake architectures.
- Strong communication and stakeholder management skills.