Data Engineer

Emagine - Portugal; Teletrabalho; BRL 180.000 - 240.000; Tempo integral

Resumo da oferta

A prominent technology company is seeking a Data / ETL Engineer experienced in AWS to build and operate data pipelines. The role requires strong SQL and Python skills, hands-on experience with Amazon Athena, and a solid understanding of AWS services. The ideal candidate should also be comfortable with modern data lake architectures and must be able to work in the Denmark time zone. This position is remote based in Brazil.

Qualificações

• Strong SQL skills, preferably with Microsoft SQL Server.
• Solid Python development skills for data processing.
• Hands-on experience with Amazon Athena.

Responsabilidades

• Build and operate data pipelines in AWS.
• Work within the Denmark time zone.

Conhecimentos

SQL

Python

AWS Glue

Amazon Athena

Apache Iceberg

Descrição da oferta de emprego

Profile

Data / ETL Engineer (AWS) We are looking for a Data / ETL Engineers with strong experience building and operating data pipelines in AWS.

Core skills & experience

• Solid understanding of relational databases, with strong SQL skills (experience with Microsoft SQL Server preferred)
• Strong Python development skills, particularly for data processing and ETL workloads
• Hands‑on experience with Amazon Athena for querying data in data lakes
• Experience with AWS Glue, including Glue Data Catalog, databases, and crawlers
• Knowledge of Apache Iceberg for table formats and data lake management
• Broad AWS knowledge, including data services, IAM, networking basics, and operational best practices

Nice-to-have / preferred experience

• Experience building streaming data pipelines, preferably using Apache Flink
• Familiarity with Kafka (managed or self-hosted) for event‑driven architectures
• Experience with non-relational datastores and / or column‑oriented data stores (e.g. NoSQL, data warehouse or analytics-focused systems)
• Comfortable working with modern data lake architectures in AWS
• Experience collaborating with engineers, analysts, and stakeholders around data models and ingestion patterns

To work in the Denmark time zone