**Tecnical skills / Hard Skills**:
- SQL: Proficiency in SQL (Structured Query Language) is essential for querying and manipulating data in relational databases.
- Programming Languages: Strong programming skills in languages such as Python, R, or Java are necessary for data manipulation, scripting, and automation tasks.
- Data Integration: Experience with scripting and tools for data integration, such as ETL (Extract, Transform, Load) processes, to connect with various data sources like databases, APIs, files, etc.
- Data Modeling: Solid understanding of data modeling concepts and techniques for designing efficient and scalable databases and data warehouses.
- Data Visualization: Proficiency in data visualization tools such as Looker Studio, Power BI, Tableau, etc., to create interactive dashboards and reports.
- Statistical Analysis: Knowledge of statistical methods and techniques for analyzing data and identifying patterns, trends, and insights.
- Data Cleaning and Preprocessing: Experience in data cleaning, preprocessing, and transformation to ensure data quality and consistency.
- Database Management Systems (DBMS): Familiarity with relational database management systems (e.g., MySQL, PostgreSQL, SQL Server) for data storage and retrieval.
- API Integration: Ability to work with APIs (Application Programming Interfaces) to extract data from web services and other external sources.
- Scripting Languages: Proficiency in scripting languages such as Bash scripting for automation tasks, especially in the context of data extraction and processing.
- Version Control Systems: Familiarity with version control systems like Git for managing and tracking changes to scripts and code.
- Data Warehousing: Understanding of data warehousing concepts and architectures for storing and organizing large volumes of data.
- Advanced/Fluent English
**Soft skills**:
- Analytical Thinking: The ability to analyze complex datasets, identify patterns, and draw meaningful insights to support data-driven decision-making.
- Problem-Solving: Strong problem-solving skills to address data-related challenges, troubleshoot issues, and propose effective solutions.
- Attention to Detail: Being detail-oriented is crucial for ensuring data accuracy, detecting anomalies, and maintaining data integrity throughout the analysis process.
- Communication Skills: Effective communication skills, both verbal and written, to convey technical concepts and insights to non-technical stakeholders in a clear and understandable manner.
- Collaboration: The capacity to work collaboratively with cross-functional teams, including business stakeholders, data engineers, and IT professionals, to understand business requirements and deliver actionable insights.
- Time Management: The ability to prioritize tasks, manage deadlines, and handle multiple projects simultaneously in a fast-paced environment.
- Adaptability: Being adaptable and flexible to navigate changes, evolving business needs, and new technologies in the dynamic field of data analysis and business intelligence.
- Creativity: Thinking creatively to explore new approaches, techniques, and visualizations for data analysis and presentation, enhancing the effectiveness of insights delivery.
- Curiosity: A curious mindset to explore data, ask insightful questions, and continuously seek opportunities for improvement and innovation in data analysis processes.
- Client Focus: A customer-centric approach to understanding the needs and expectations of stakeholders, delivering solutions that add value and drive business outcomes.
- Continuous Learning: A commitment to continuous learning and professional development to stay updated on emerging technologies, tools, and best practices in data analysis and business intelligence.
Tipo de vaga: Tempo integral, Efetivo CLT
Pagamento: a partir de R$3.000,00 por mês
**Benefícios**:
- Assistência médica
- Assistência odontológica
- Vale-refeição
- Vale-transporte
Horário de trabalho:
- De segunda à sexta-feira
- Turno de 8 horas
- Turno diário