Data Quality Analyst

Role Overview

As a Data Quality Specialist within the IT division, you will be part of an agile team dedicated to ensuring the highest standards of data quality across selling, ordering, and provisioning systems. You will serve as both a coordinator and subject matter expert in the development, implementation, and execution of data analysis, protection, and cleansing processes.

Key Responsibilities

• Define scope and objectives to enhance and safeguard data quality across BSS and OSS systems, processes, and applications.
• Establish and maintain processes and agreements with business units to ensure optimal data quality and implement corrective actions when necessary.
• Collaborate with Data Quality Reporting and Data Governance teams to define requirements and drive improvements.
• Partner with leaders in Sales, Finance, Marketing, and Product Analytics to identify and address data quality issues affecting analytical insights.
• Advocate for the benefits of high-quality data and communicate its value across the organization.
• Participate in Data Quality Remediation programs and conduct Root Cause Analysis.
• Coordinate data cleansing activities across teams and provide reporting through dashboards.
• Develop and implement efficient Data Quality control metrics.
• Design, implement, and maintain automation tools for data cleansing.

Required Skills & Qualifications

• Master’s degree in IT, Applied Economics, or equivalent experience (minimum 5 years in data management).
• Proven expertise in data quality management, including data auditing, analysis, and cleansing.
• Strong analytical skills with the ability to deconstruct complex problems.
• Excellent communication skills, adaptable to various stakeholder levels.
• Quick learner with proficiency in new tools and technologies related to data and IT.
• Expert-level SQL/PostgreSQL/PySQL knowledge (Oracle, Teradata, Sybase).
• Advanced proficiency in OpenVMS, Unix/Linux, and ACMS.
• Deep understanding of mobile technologies (NGIN, OCS, HLR, etc.).
• Skilled in scripting languages: COBOL, Java, Python, Shell, DCL.
• Familiarity with Big Data tools (Hadoop, Hive & Spark) and ability to contribute to ML/AI projects is a plus.
• Knowledge of cloud technologies including Microsoft Azure and Oracle Cloud Infrastructure (OCI).
• Familiarity with Databricks is required.
• Experience with version control systems (e.g., Git).
• Agile mindset with the ability to act as Scrum Master or Product Owner.
• Knowledge of GDPR and ePrivacy regulations.
• Fluent in English (spoken and written).