Data Analyst

Há 2 dias

Lisboa, Lisboa, Portugal Randstad Digital Portugal Tempo inteiro

Randstad Digital, we are based on the excellence of our engineers, and consider our team to be our most valuable asset. Always putting talent first, we support technology specialists throughout their professional lives and ensure that they develop their skills.

We provide varied and challenging career opportunities, as we work with our clients on a wide range of projects in various industries, including Automotive, Heavy Industry, Transportation, Finance, Services, Security and Biometrics, Platforms and IoT, Telecommunications, and Mobile Communications, among others.

Our mission is to be a trusted digital enablement partner that facilitates the accelerated transformation of companies by providing talent, capacity, and global solutions in specialized domains. We support four service lines, including customer experience, digital and product engineering, data and analytics, and cloud transformation, as well as three engagement models, including talent services, global talent centers, and managed solutions capabilities.

Responsibilities

The candidate would work as part of a couple of Agile teams dedicated to the development and maintenance of reporting solutions with high levels of criticality and a complex data model in place. Among the main responsibilities, the candidate would participate actively on the analysis, estimation and development of customized solutions for different business units within the company, and would collaborate with other team members placed in Spain and India.

Qualifications

  • Data analysis using multiple data sources (ERP, CRM, SQL, APIs, etc.).
  • Design of efficient data models. Solid experience in data modelling.
  • Experience with ETL/ELT Processes, ensuring quality and efficiency.
  • Development of reporting solutions in PBI, Tableau, Qlik, Thoughspot, etc.
  • Wide experience in collaboration with business partners for collection of new requirements and translation into technical solutions.
  • Bachelor's degree in computer science, mathematics, or statistics preferred.
  • Solid experience in Finance.
  • Fluent in English.

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