CIEE - Centro de Integração Empresa-Escola

Data Engineer

• Define and evolve the corporate data architecture (conceptual, logical, and physical).
• Create and standardize data models for transactional systems, analytics, and integrations.
• Define storage patterns (Data Warehouse, Data Lake, Lakehouse, NoSQL, relational databases).
• Select and recommend appropriate technologies such as Oracle, SQL Server/Azure, AWS (Redshift, S3), Google BigQuery, among others.
• Design modern cloud-based architectures (public, private, or hybrid).
• Structure analytical models (e.g., star schema, snowflake) for BI and analytics.
• Ensure data integrity, consistency, and traceability.
• Define integration standards and ETL/ELT pipelines.
• Design integrations between internal and external systems.
• Collaborate with Data Engineering to build pipelines.
• Define guidelines for data governance, quality, and security.
• Ensure compliance with regulations such as LGPD and GDPR.
• Structure and support the creation of data catalogs and data dictionaries.
• Support BI and Data Science teams in the structured provisioning of data.
• Ensure performance, scalability, and optimization of queries and analytical environments.
• Participate in technical forums and architecture committees to ensure adherence to corporate principles.
• Evaluate trade-offs between cost, performance, security, and scalability in architectural decisions.

Data Architect – Senior

Architect

• Serve as the guardian and steward of Business Architecture.
• Translate corporate strategy and strategic objectives into capability maps.
• Connect strategy, portfolio and execution.
• Work collaboratively with Enterprise Architects and IT.
• Support the definition and evolution of the operating model, organizational design and governance.
• Facilitate high-level strategic workshops.
• Support organizational and digital transformation initiatives.
• Act as a strategic advisor to executives and leadership.
• Use and evolve Enterprise Architecture tools.
• Promote a culture of architectural thinking and value orientation.

Business Architect

Data Scientist

• Develop predictive and machine learning models to solve business problems (churn, demand forecasting, segmentation, etc.)
• Conduct advanced statistical analyses and controlled experiments (A/B tests, causal inference)
• Perform exploratory data analysis to identify patterns, trends and opportunities
• Communicate results and recommendations clearly to technical and non-technical stakeholders
• Define evaluation metrics and monitor model performance in production
• Act as a technical reference in data science, guiding best practices and methodologies
• Collaborate with data engineers to ensure the availability and quality of required data

Senior Data Scientist

• Design, develop and maintain data pipelines (ETL/ELT) for data ingestion and transformation
• Implement and maintain data models (star schema) optimized for analytical consumption
• Write and optimize SQL queries for processing large volumes of data
• Develop Python scripts to automate data processes
• Monitor data quality through validations and automated tests
• Collaborate with BI Analysts and Data Scientists to ensure data availability and reliability

Data Engineer – Mid-Level

Business Intelligence Developer

• Develop Power BI dashboards and reports to meet business area requirements
• Gather requirements from stakeholders to define metrics and KPIs
• Build and maintain dimensional data models to support BI solutions
• Write SQL queries for data extraction, transformation, and validation
• Document BI solutions (data dictionary, business rules, data flows)

Data Architect – Senior

Business Architect

Senior Data Scientist

Data Engineer – Mid-Level

BI Analyst, Mid-level