AnalistadeDados-EngenhariadeDados

## Accountabilities In this role, you will be responsible for working across the data engineering and analytics lifecycle to ensure reliable, structured, and high-quality data availability for business use. Your work will directly support analytics, reporting, and strategic decision-making through robust data pipelines and systems. Collect, extract, and integrate data from multiple primary and secondary sources, ensuring consistency and usability. Clean, transform, and organize large datasets, removing irrelevant or inconsistent information. Analyze structured and unstructured data using statistical and analytical techniques to identify trends and insights. Design, build, and maintain databases, data pipelines, and data storage solutions to support analytical needs. Develop and support ETL processes using industry-standard tools and frameworks. Identify opportunities to improve data processes, performance, and overall data platform efficiency. Troubleshoot data issues, resolve pipeline failures, and ensure stability of data systems. Support and monitor data platforms, ensuring availability, reliability, and performance for end users. Requirements You should have a strong technical foundation in data engineering and analytics, with experience handling large datasets and building reliable data systems. A solid understanding of data architecture, ETL processes, and programming is essential, along with the ability to work independently in complex environments. Degree in Information Technology or related field, or postgraduate specialization (minimum 360 hours) in a relevant area. Around 2 years of experience in data extraction, modeling, and handling large-scale datasets for analytics. Strong knowledge of SQL, Python (Pandas), and Shell Script or similar languages. Experience with ETL tools such as Pentaho, Talend, SSIS, Apache NiFi, or equivalents. Familiarity with databases such as Oracle, SQL Server, and PostgreSQL. Knowledge of cloud storage solutions such as AWS S3