Data Engineer, Mid-level

Jobtailor; Barueri; Presencial; BRL 150 000 - 210 000; Tempo integral

Resumo da oferta

Jobtailor in São Paulo, Brazil seeks a data engineer to design, develop, and maintain data pipelines across batch and streaming workloads. You will implement cloud data architectures, ensure data quality and traceability, and collaborate with data scientists and ML engineers to operationalize models.

Responsibilities include integrating heterogeneous data sources, deploying DataOps practices, and documenting architectural decisions to support scalable analytics across multi-cloud environments.

Qualificações

• Experience developing and maintaining data pipelines in cloud and multicloud environments.
• Knowledge of tools such as Apache Spark, Airflow, dbt or equivalents.
• Implementation and management of cloud data architectures (Azure, AWS, or GCP).
• Ensuring data quality and data governance.
• Integration of heterogeneous data sources (APIs, relational databases, NoSQL, flat files).
• Collaboration with data scientists and ML engineers.
• Deployment of DataOps practices.

Responsabilidades

• Design, develop, and maintain data pipelines (batch and streaming).
• Implement and manage cloud data architectures.
• Ensure data quality and traceability.
• Integrate heterogeneous data sources.
• Collaborate with data scientists and ML engineers.
• Document solutions and architectural decisions.

Conhecimentos

Data pipelines

Cloud data architectures

Data governance

Collaboration with data scientists

Data quality

Ferramentas

Apache Spark

Airflow

dbt

Descrição da oferta de emprego

Responsibilities

• Design, develop, and maintain data pipelines (batch and streaming)
• Implement and manage cloud data architectures
• Ensure data quality and traceability
• Integrate heterogeneous data sources
• Collaborate with data scientists and ML engineers
• Document solutions and architectural decisions

Requirements

• Experience developing and maintaining data pipelines in cloud and multicloud environments
• Knowledge of tools such as Apache Spark, Airflow, dbt or equivalents
• Implementation and management of cloud data architectures (Azure, AWS, or GCP)
• Ensuring data quality and data governance
• Integration of heterogeneous data sources (APIs, relational databases, NoSQL, flat files)
• Collaboration with data scientists and ML engineers
• Deployment of DataOps practices