Data Analyst

As a Data Analyst, you will play a crucial role in managing, analyzing, and interpreting data to support
business decision-making. You will be responsible for overseeing the messaging data set, defining data
trapping points, and ensuring the accuracy of data models for reporting, monitoring, and SLA tracking. Your
work will directly impact the organization's ability to achieve its goals through data-driven insights and
optimized processes.

Roles and Responsibilities:
As a Data Analyst, you will play a crucial role in managing, analyzing, and interpreting data to support
business decision-making. You will be responsible for overseeing the messaging data set, defining data
trapping points, and ensuring the accuracy of data models for reporting, monitoring, and SLA tracking. Your
work will directly impact the organization's ability to achieve its goals through data-driven insights and
optimized processes.
1. Manage Messaging Data Set:
o Oversee the collection, organization, and maintenance of the messaging data set.
o Ensure the data is accurate, up-to-date, and accessible to relevant stakeholders.
o Collaborate with cross-functional teams to understand data requirements and implement effective
data management strategies.
2. Data Trapping Points Management:
o Identify key data trapping points within the messaging channels to capture relevant data elements.
o Design and implement data trapping mechanisms to ensure comprehensive data collection.
o Continuously monitor and optimize data trapping processes to enhance data quality and efficiency.
3. Data Model Definition:
o Develop and define data models to support various business needs, including reporting, monitoring,
and SLA tracking.
o Work closely with the data architecture team to ensure alignment with the overall data strategy.
o Regularly update and refine data models to reflect changes in business requirements or data
sources.
4. Data Element Definition and Documentation:
o Identify and define critical data elements required for accurate and meaningful reporting.
o Create and maintain a detailed repository of data elements, including definitions, sources, and usage
guidelines.
o Ensure that all data elements are documented in a clear and consistent manner to support data
governance and compliance efforts.
5. Data Process Flow Definition:
o Map out the data process flow for messaging channels, identifying key steps and potential
bottlenecks.
o Document the end-to-end messaging process, including data inputs, processing, and outputs.
o Define and implement data traps at each stage of the process to capture essential data elements.
6. Data Model Documentation and Maintenance:
o Develop comprehensive documentation for all data models, including assumptions, calculations, and
dependencies.
o Ensure that all documentation is up-to-date, accurate, and accessible to relevant stakeholders.
o Regularly review and update data models to ensure they remain aligned with the Draft Data
Architecture for the UMF (Unified Messaging Framework).
7. Reporting and Analysis:
o Develop and deliver reports, dashboards, and visualizations that provide actionable insights to
stakeholders.
o Conduct in-depth analysis of messaging data to identify trends, patterns, and opportunities for
improvement.
o Present findings and recommendations to senior management and other stakeholders to support
data-driven decision-making.
8. Collaboration and Communication:
o Collaborate with other data analysts, data engineers, and business analysts to ensure data
consistency and alignment across the organization.
o Communicate complex data concepts and analysis results to non-technical stakeholders in a clear
and understandable manner.
o Participate in regular meetings with cross-functional teams to discuss data-related challenges and
opportunities.
9. Continuous Improvement:
o Stay up-to-date with the latest trends, tools, and best practices in data analysis and management.
o Continuously seek opportunities to improve data processes, tools, and methodologies to enhance
the quality and efficiency of data analysis.
o Provide mentorship and guidance to junior data analysts and other team members as needed.
Qualifications:
• Education: Bachelor’s degree in Data Science, Statistics, Computer Science, Information Systems, or a
related field.
• Experience: Minimum 5 years of experience in data analysis, data management, or a related field.
Experience in managing messaging data sets is preferred.
• Technical Skills:
o Proficiency in data analysis tools such as SQL, Python, R, or similar.
o Experience with data visualization tools like Power BI, Tableau, or similar.
o Knowledge of data modeling techniques and tools.
o Familiarity with messaging systems and data trapping techniques.
• Soft Skills:
o Strong analytical and problem-solving skills.
o Excellent communication and presentation skills.
o Ability to work collaboratively in a team environment.
o Attention to detail and a commitment to accuracy