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-makingTo 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.