Data Business Analyst

Description

QStaffers is currently looking for a Data Business Analyst for one of our partners, a global leader in the IT Services and IT Consulting.

Key Responsibilities

Ensure and manage bridging the gap between business stakeholders and technical teams.

Managing the activities of receiving new Requirements and how to translate the Data Business Requirements to Technical Solution through conducting the Data engagement with business and Solution Design and supporting the Product Owners throughout the whole process.

Effectively use the Data Warehouse Tools in fulfilling the Bank's different needs to provide successful and operational solutions. Ensuring all changes and activities are documented accurately and maintained throughout the implementation phases.

Ensure data is handled ethically and all processes are undertaken in compliance with company policy, internal controls, data protection legislation and relevant national / industry standards.

Identify opportunities through which to deliver process efficiency / improvement and develop business proposals through which to communicate and deliver the change.

Build and maintain strong collaborative relationships with senior internal stakeholders, subject matter experts and external clients.

Ensure that the Solution is utilizing the Different Teams Roles and Responsibilities bearing in mind the Strategic approach within the different Teams and the Business

Engage during the testing phase to ensure that everything aligns with expectations. In cases involving technical advancements.

Requirements

Bachelor's degree in Computer Science, Information System or a related field.

510 years of experience in Business Analysis and Solution Design.

Minimum 3+ years of experience working with Data Warehouse (DWH) environments.

Strong numerical and analytical skills with the ability to interpret complex datasets.

Knowledge of statistical tools and analytical technologies for data analysis and insight generation.

Good understanding of various data tools and end-to-end data flows across systems.

Ability to identify trends, analyze variances, and highlight exceptions, risks, and opportunities to support decision-making.