Data Analyst (Advanced SQL) 12-Months Contract - Part-Time

Our client is a leading global technology company with a strong presence in digital platforms, innovation, and large-scale software systems. They are currently seeking a highly analytical and business-focused Data Analyst to drive data-driven decision-making, operational excellence, and strategic insights across a large-scale customer support and business operations environment.

This is a 12-months contract role.

Responsibilities

• Analyze large and complex datasets using SQL, Python/R, Tableau, Hive, Presto, and other big data technologies.
• Develop and execute data science and analytics initiatives that support business strategy and operational performance.
• Design, build, and maintain advanced analytical models, dashboards, and reporting frameworks to generate actionable insights.
• Partner with cross-functional stakeholders to identify opportunities, solve business challenges, and drive continuous improvement.
• Present data-driven recommendations and insights to both technical and non-technical audiences, including senior leadership.
• Establish scalable reporting systems, performance metrics, and KPIs to support operational efficiency and decision-making.
• Mentor analysts and contribute to best practices in analytics, reporting, and data science.

Requirements

• 2 years of experience in data analytics, data science, business intelligence, or operational support within a technical environment.
• Advanced SQL skills, including developing, optimizing, and maintaining complex queries.
• Hands-on experience with data visualization and big data tools such as Tableau, Hive, Presto, Python, or R.
• Strong understanding of operational metrics, KPI development, reporting architecture, and data pipelines.
• Proven ability to translate complex data into clear business insights and strategic recommendations.
• Excellent communication and stakeholder management skills, with the ability to influence decision-making at multiple levels.
• Experience working with large-scale datasets and delivering measurable business outcomes through analytics.
• Exposure to customer operations, support organizations, or scaled service environments is advantageous.