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Data Insights & Visualization Analyst – SQL, Python, BI & Dashboards

Exclusive opportunity

Hybrid

Data Insights & Visualization Analyst – SQL, Python, BI & Dashboards

Accenture

Data Insights & Visualization Analyst – SQL, Python, BI & Dashboards

Skills

Google Cloud PlatformSQL QueriesData MiningPythonRData AnalysisAI

1 month ago

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Important information


Contract type:

Permanent

Location:

Metro Manila, Philippines

Work mode:

Hybrid

Published on:

9 September 2026

What they need


Turn complex data into clear, interactive insights that drive real decisions.

Do you love working with data and telling its story through dashboards and reports? Join Accenture as a Data Analyst and build interactive tools that help businesses understand and act on their data — powered by modern BI and (Gen)AI capabilities.

What You'll Do

  • Wrangle, analyze, and prepare data to deliver relevant, timely, and actionable insights
  • Build and maintain interactive dashboards, reports, and BI artifacts using modern visualization tools
  • Translate business requirements into analytical tasks — surfacing data gaps, issues, or ambiguities
  • Run data extraction, preparation, validation, recurring analysis, testing, and documentation
  • Use SQL to work with large, complex datasets; use Python or R for deeper analysis and automation
  • Build and maintain reports, workflows, and analytical data structures using internal BI tools
  • Use and customize**(Gen)AI and AI-powered visualization** capabilities to enable a dialog with data
  • Collaborate with consultants, developers, and data engineers to test logic and refine solutions

What You'll Need

  • Minimum 2 years (typically 2–3+) in a data or analytics role; customer-facing experience is a plus
  • Strong SQL skills for querying large or complex datasets
  • Working knowledge of BI/reporting tools, data modeling, ETL, and analytical/warehouse architectures
  • Experience with large enterprise datasets and the ability to quickly learn new internal analytics tools
  • Python or R (e.g., via Colab) is a strong plus; cloud/GCP exposure is useful but secondary

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