Dados e analytics · Não informado

Senior Data Engineer

BEESCampinas, São Paulo, Brazil

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A vaga é para Senior Data Engineer na BEES. O modelo informado é não informado; localidade: Campinas, São Paulo, Brazil. At BEES, we dream big, lead with purpose, and develop technology that transforms the way retailers and sellers grow. Contribute to obtaining knowledge in the business context and creating new data products to meet their strategic and operational needs.

Resumo automático baseado somente nas informações publicadas pela empresa.

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  1. Dados e analytics

    Muito alta · 5/5

    No título da vaga · 2 menções

  2. Senioridade · Sênior

    Muito alta · 5/5

    Nível indicado no título

  3. IA e automação

    Média · 3/5

    Na descrição · 2 menções

  4. Segurança

    Média · 3/5

    Na descrição · 2 menções

Escala de 1 a 5. Mede presença e posição no anúncio; não mede sua chance de contratação.

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Contexto da oportunidadeAbrirFechar

About BEES

Join us to build the future of B2B commerce!

BEES is AB InBev’s B2B platform. Through our ecosystem, merchants and retailers across 29 countries can stock their businesses quickly, easily, and securely. At BEES, we dream big, lead with purpose, and develop technology that transforms the way retailers and sellers grow.

Every line of code and every partnership is built in service of a single mission: to make commerce better for retailers and sellers around the world. Here, your work is not just important. It makes a difference!

What you'll doAbrirFechar

Leads efforts within the organization to drive the development and maintenance of data services and solutions to support products, downstream services, or infrastructure tools and platforms used across BEES.

Design efficient data models and understand concepts such as normalization, denormalization, and dimensional modeling.

Implement improvements in architecture and processes to improve the performance, monitoring, and evolution of data products.

Develop and maintain data ingestion, processing, control/security, and data provisioning processes for different consumers (services, front-end, among others).

Contribute to obtaining knowledge in the business context and creating new data products to meet their strategic and operational needs.

What you'll need:

Degree in Computer Science, Computer Engineering, Information Systems, Systems Development Analysis or similar;

Advanced English;

Assess scalability, reliability, security, and compliance implications of data pipeline designs.

Understand cloud computing platforms and services offered by providers like AWS, Azure, and Google Cloud.

Evaluate programming solutions in Python, PySpark, Scala, and SQL for data processing and analysis.

Evaluate data quality processes and controls to ensure accuracy and completeness.

Apply debugging techniques to identify and resolve cross-module issues.

Implement monitoring, alerting, and failure handling mechanisms in architecture designs.

Assess effectiveness of CI/CD principles and practices in automated pipelines.

Design, develop, and maintain APIs for data exchange between applications.

Apply Agile practices to plan, execute, and deliver data engineering tasks and projects.

Logical reasoning and analytical skills;

Meeting deadlines and quality of work;

Effective and transparent dialog with other areas and co-workers;

Ability to communicate and interpersonal relationships to to present cases and discuss them with other areas involved;

Being independent in activities;

Work as part of a team, promoting a good relationship with the team;

Evaluate data pipeline solutions for latency, throughput and accuracy.

Analyze data requirements and business needs to inform data modeling decisions.

Understand the principles and assumptions of different machine learning capabilities.

Integrate data sets with visualization tools to create insightful reports and dashboards

More about you:

Logical reasoning and analytical skills;

Meeting deadlines and quality of work;

Effective and transparent dialog with other areas and co-workers;

Ability to communicate and interpersonal relationships to to present cases and discuss them with other areas involved;

Being independent in activities;

Work as part of a team, promoting a good relationship with the team;

Evaluate data pipeline solutions for latency, throughput and accuracy.

Analyze data requirements and business needs to inform data modeling decisions.

Understand the principles and assumptions of different machine learning capabilities.

Integrate data sets with visualization tools to create insightful reports and dashboards

What We Offer:

Performance based bonus*

Attendance Bonus*

Private pension plan

Meal Allowance

Casual office and dress code

Days off*

Health, dental, and life insurance

Medicines discounts

WellHub partnership

Childcare subsidies

Discounts on Ambev products*

Clube Ben partnership

Scholarship*

School materials assurance

Language and training platforms

Transport allowance

*Rules applied

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