Data Analyst — SQL/Python | Power BI Dashboards

PPG

Laza

Híbrido

EUR 36.000 - 60.000

Jornada completa

Hace 3 días
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Descripción de la vacante

PPG is seeking a detail-oriented Data Analyst to transform raw data into actionable insights and support business decision-making. The role focuses on analyzing large datasets with SQL and Python and presenting findings through Power BI dashboards.

You will collaborate with stakeholders to understand needs and deliver data-driven solutions. The position emphasizes data quality, reporting processes, and advancing the organization’s data maturity, with in-person work Monday-Thursday and Flexible

Formación

  • Proven experience as a Data Analyst or similar role.
  • Strong skills in SQL and Python (e.g., pandas, numpy).
  • Experience with Power BI for dashboards and reporting.
  • Solid understanding of data modelling and ETL concepts.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to translate data into business insights.

Responsabilidades

  • Collect, clean, and validate data from multiple sources to ensure accuracy.
  • Analyze datasets using SQL and Python to identify trends and insights.
  • Build and maintain interactive dashboards and reports in Power BI.
  • Collaborate with stakeholders to understand business needs and deliver solutions.
  • Monitor data quality and suggest improvements to data processes.
  • Document methodologies, analysis, and key findings.

Conocimientos

SQL
Python
Power BI
Data analysis
Data modelling
ETL concepts
Communication
Analytical thinking

Herramientas

pandas
numpy

Descripción del empleo

PPG is seeking a detail-oriented Data Analyst to transform raw data into actionable insights and support business decision-making. The role focuses on analyzing large datasets with SQL and Python and presenting findings through Power BI dashboards.

You will collaborate with stakeholders to understand needs and deliver data-driven solutions. The position emphasizes data quality, reporting processes, and advancing the organization’s data maturity, with in-person work Monday-Thursday and Flexible

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