Data engineer iii

NetVagas; São Paulo; Teletrabalho; BRL 60.000 - 120.000; Tempo integral

Resumo da oferta

Uma empresa inovadora está em busca de um Engenheiro de Dados para apoiar desenvolvedores e cientistas de dados em iniciativas de dados. Esta função emocionante envolve a criação de pipelines de dados otimizados e a construção de ferramentas analíticas que fornecem insights acionáveis sobre aquisição de clientes e eficiência operacional. Com um ambiente de trabalho remoto, a posição oferece a oportunidade de colaborar em projetos globais, onde suas contribuições podem impactar significativamente o desempenho do negócio. Se você é apaixonado por dados e deseja fazer parte de uma equipe dinâmica, esta é a oportunidade perfeita para você.

Serviços

Trabalho 100% remoto

Horário flexível

Projetos globais

Ambiente colaborativo

Qualificações

• Experiência avançada em SQL e bancos de dados relacionais.
• Histórico de construção e otimização de pipelines de dados.
• Habilidade em análise de dados não estruturados.

Responsabilidades

• Criar e manter a arquitetura ideal de pipelines de dados.
• Identificar e implementar melhorias de processos internos.
• Trabalhar com equipes multifuncionais para resolver problemas de dados.

Conhecimentos

SQL

AWS

Python

Data Pipeline Architecture

Data Transformation

ETL Processes

Azure DevOps

Data Modeling

Big Data Technologies

Cross-Functional Team Collaboration

Ferramentas

Azure SQL Database

Azure Data Factory

Azure Synapse

Azure Databricks

Azure Functions

Data Lake

Azure Log Analytics

Cosmos DB

Descrição da oferta de emprego

The Data Engineer will support our software developers, database architects, data analysts, and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.

Responsibilities for Data Engineer:

1. Create and maintain optimal data pipeline architecture.
2. Assemble large, complex data sets that meet functional/non-functional business requirements.
3. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
4. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies.
5. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
6. Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs.
7. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
8. Work with data and analytics experts to strive for greater functionality in our data systems.

Qualifications for Data Engineer:

1. Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL), as well as working familiarity with a variety of databases.
2. Experience building and optimizing big data pipelines, architectures, and data sets.
3. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
4. Strong analytic skills related to working with unstructured datasets.
5. Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
6. A successful history of manipulating, processing, and extracting value from large disconnected datasets.
7. Working knowledge of message queuing, stream processing, and highly scalable big data stores.
8. Strong project management and organizational skills.
9. Experience supporting and working with cross-functional teams in a dynamic environment.
10. Proficiency in building out scalable and reliable ETL pipelines and processes to ingest data from a variety of data sources including but not limited to SharePoint, REST API, Blob Storage.
11. Proficiency in Azure PaaS offerings and data engineering target architecture, including but not limited to Azure SQL database, Azure Data Factory, Azure Synapse, Azure Databricks, Azure Functions, Data Lake, Azure Log Analytics.
12. Proficiency in large dataset transformation using Python.
13. Proficiency in relational databases and SQL, including but not limited to stored procedures, indexes, functions, and triggers.
14. Proficiency in Azure DevOps CI/CD and Git Repository.
15. Deep understanding in data model design and relational database normalization.
16. Familiarity with Non-SQL databases, e.g., Cosmos DB.

Additional Information:

1. 100% WFH
2. Global project - Fluent English is mandatory, Spanish is nice to have.
3. Work time: 10AM - 7PM
4. Location: Brasil
5. Mode of work: Remote