Job Description
Mission:
- To elevate the organization's data maturity by ensuring data quality, utilizing big data technologies for advanced analytics, and translating insights into actionable strategies for data-driven decision-making and digital transformation.
- To ensure data quality and integrity through monitoring, implementation of best practices, and leveraging big data technologies to extract valuable insights and drive business value.
Roles & Responsibilities:
- To support the team in the development and implementation of data quality metrics, monitoring data quality over time, and directly identifying and resolving data quality issues.
- To work closely with cross-functional teams to ensure alignment with data quality standards and efficient data utilization to drive business value.
- To identify and execute possible opportunities to leverage big data technologies to create business value aligned with digital transformation initiatives in the data dimension.
- To execute data integrity audits while working closely with the Marketing data science team and other relevant stakeholders.
- To develop and implement robust data integration and validation processes to ensure the accuracy and completeness of transferred information.
- To check revenue flow, free usage, and overall system health from both financial and non-financial perspectives.
- To utilize big data technologies such as Open-Source databases and apply advanced statistical and exploratory analytical techniques to analyze vast datasets, extract valuable insights, interpret complex data, and uncover patterns and anomalies.
- To develop and implement data models and algorithms to optimize data processing and enhance decision-making processes.
- To utilize data visualization tools to present findings and communicate key insights to stakeholders.
- To ensure adherence to data governance principles aligned with the data management and analytics framework.
- To stay abreast with industry trends and emerging technologies in big data analytics to ensure the best methods and techniques are used in data analytics.
- To identify opportunities for process optimization and efficiency improvements within the data management and analytics framework.
- To identify business requirements through collaboration with internal stakeholders and translate them into actionable analytical tasks.
- To document processes, methodologies, and findings to facilitate knowledge sharing and ensure organizational continuity.
- To ensure data integration and reporting, and address any challenges and issues through coordination with relevant departments.
- To ensure the smooth transfer of customer data and safeguard the integrity of business intelligence (BI) and Big Data Systems during migration from the current system to the new system.
- To work with channels to ensure seamless integration with the new charging system and accurate reporting of service prices.
- To work closely with cross-functional teams to identify business objectives and provide data-driven inputs to optimize operations, improve customer experience, and drive growth.
- To assist in the clarification of the data integrity project’s scope in collaboration with key stakeholders.
- To build and optimize seamless data pipelines to ensure data accuracy, completeness, and accessibility, empowering informed decision-making
- To support the team in the development and execution of a transformative big data strategy, aligned with commercial objectives.
- To assist in the elevation of the organization's digital maturity and fuel data-driven innovation across all aspects related to big data technologies.
Education:
- Bachelor’s degree in Information Technology or related fields.
- An MBA degree or a Master’s degree is advantageous.
Experience:
- Technical data handling tracks record of 3 years or more, with at least one year in telecommunication-related business (CVM, BI, data engineering, and data science).
- 2 years of experience in managing a portfolio of technical and business projects.
- Working across diverse cultures and geographies is advantageous.
Technical Competencies:
- Data Architecture.
- Requirement Analysis.
- Database Management.
- Big Data Platforms.
- Reporting and Analysis.
- Data Visualization & Presentation.
- Strategy Management.
- Machine learning.
- Programming Languages.
- Business Intelligence.
- Distributed Computing.
- Statistical Analysis.
- Data Quality Assurance.
Behavioral Competencies:
- Leadership.
- Innovation.
- Relationship.
- Integrity.
- Can-do.
- Customer Centricity.
- Agility.