Analista de Dados Pleno
New
J
JobgetherData Analytics
BrazilFull-TimeMiddle
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Required Skills
- AWSPythonSQLETLAirflowRedshift
Requirements
- Solid experience in data analysis and data engineering within large-scale or complex environments.
- Strong hands-on experience with AWS cloud services, particularly S3, Redshift, Glue, or similar technologies.
- Advanced experience with data orchestration tools such as Kestra, Airflow, or equivalent platforms.
- Advanced SQL skills, including query optimization, data modeling, complex queries, and procedures.
- Advanced Python skills applied to data engineering, automation, integrations, and scripting.
- Practical experience developing ETL processes, data validations, system integrations, and automated workflows.
- Experience with RPA or process automation using tools such as Selenium, scripts, or integrations with legacy systems.
- Experience with analytical data modeling, including Data Warehouse and Data Lake architectures.
- Experience integrating multiple data sources and complex systems, as well as familiarity with BI tools and data consumption requirements.
- Experience delivering end-to-end data projects spanning architecture, development, deployment, and ongoing support.
- Strong communication skills and the ability to influence both technical teams and business stakeholders.
Responsibilities
- Lead the design and evolution of cloud-based data architecture, ensuring scalability, performance, reliability, and governance.
- Design and implement robust, resilient, and efficient data pipelines, establishing technical standards for modeling, ingestion, orchestration, and data quality.
- Serve as a technical reference for the team, supporting the development of more junior professionals and contributing to key architecture and technology decisions.
- Lead complex data integration initiatives involving ERP, e-commerce, CRM, franchises, and other business systems.
- Ensure data consistency, quality, traceability, and reliability throughout the entire data lifecycle.
- Partner closely with business stakeholders to translate strategic challenges into practical, scalable data solutions.
- Advance DataOps, CI/CD, automation, and pipeline observability practices while supporting the continuous evolution of the existing environment.
- Optimize data infrastructure costs and performance and contribute to the development of an omnichannel data vision and semantic data layer.
- Support automation initiatives involving ETL processes, validations, integrations, RPA, and legacy systems.
View Full Description & ApplyYou'll be redirected to the employer's site
