at Capgemini
ConsultanciesPosted 6 days ago
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**Senior Data Analyst** at Capgemini Engineering: Lead projects transforming complex data into actionable insights, driving business decisions with GCP (BigQuery focus). Key responsibilities: data analysis, GCP tool use, EDA, dashboard creation, and data quality assurance. Proven experience in cloud-scale analytics and data-driven problem-solving skills required.
- Compensation
- Not specified
- City
- Lisbon
- Country
- Portugal
Currency: Not specified
Full Job Description
CAPGEMINI ENGINEERING
At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the worlds most innovative companies unleash their potential. From autonomous cars to lifesaving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities.
Where you can make a difference. Where no two days are the same.
YOUR ROLE
Data Analyst GCP Focus
We are seeking a Data Analyst with a strong analytical mindset and solid hands-on experience with Google Cloud Platform (GCP) to join our project team. The successful candidate will transform complex data into actionable insights, supporting business decision-making through analysis, reporting, and data visualization, with a strong emphasis on BigQuery and cloud-scale analytics.
Key Responsibilities
- Take ownership of data analysis initiatives, demonstrating a proactive, detail-oriented, and results-driven approach
- Analyze, transform, and interpret complex datasets to generate actionable insights and support data-driven business decisions
- Collaborate closely with business stakeholders and cross-functional teams to gather requirements and translate them into analytical solutions
- Design, build, and maintain efficient queries, data models, and datasets using GCP tools, with a strong focus on BigQuery
- Perform exploratory data analysis (EDA) to identify trends, patterns, anomalies, and opportunities
- Ensure data quality, consistency, and reliability through validation processes, monitoring, documentation, and dataset labeling
- Develop and maintain dashboards, reports, and KPIs, enabling business users to monitor performance and make informed decisions
- Use cloud-based and big data technologies to process and analyze large volumes of structured and semi-structured data
- Communicate insights, findings, and recommendations clearly to both technical and non-technical stakeholders
- Promote a data-driven culture by supporting best practices in analytics, reporting, and data governance
