Data Analyst

July 9, 2026
Application ends: October 7, 2026

Job Description

REQUIREMENTS

  • Strong analytical and problem-solving skills with the ability to translate business requirements into technical solutions.
  • Excellent communication and collaboration skills for effective teamwork.
  • Proficiency in developing dashboards and reports using Power-BI.
  • Experience with data warehousing concepts, including dimensional modeling and ETL processes.
  • Bachelor’s or Master’s degree in Engineering, Computer Science, or related discipline.
  • Minimum 8 years of professional experience, with at least 4 years in the Business Intelligence domain.
  • Proven experience with Power-BI (desktop and web app) and expertise in building semantic models for data visualization.
  • Proven experience with Alteryx or other ETL tools, and advanced SQL skills including complex queries and database performance optimization.

RESPONSIBILITIES

Data Management and ETL

  • Extract, transform, and load (ETL) data utilizing Alteryx and Databricks from various sources into data warehouses or data lakes.
  • Design and optimize data models utilizing ETL tools or SQL queries to enable efficient data analysis and visualization.

Dashboard and Reporting

  • Develop and maintain interactive dashboards and reports using Power-BI (desktop and web app) to visualize key performance indicators and business metrics.
  • Implement data quality checks and ensure data integrity across different data sources.

Collaboration and Improvement

  • Collaborate with cross-functional teams to gather requirements and translate business needs into actionable insights.
  • Continuously monitor and evaluate BI solutions to identify opportunities for improvement and optimization.
  • Conduct ad-hoc analysis of significant deviations between measurement results and performance targets, suggesting process improvements.

Performance and Process Enhancement

  • Identify ways to improve process efficiency by leveraging data analytics techniques and process re-engineering.
  • Rollout of measurement automation and analytics reporting tools to enhance process performance KPIs.

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