Data Engineer

Emagine - Portugal; Teletrabalho; BRL 80.000 - 120.000; Tempo integral

Resumo da oferta

A data solutions company is seeking a skilled Data / ETL Engineer to develop and manage data pipelines in AWS. The ideal candidate has substantial experience with SQL, Python, and various AWS services, especially AWS Glue and Amazon Athena. Familiarity with streaming data pipelines and modern data lake architectures is preferred. Applicants should be able to work effectively across teams while maintaining a focus on best practices in data management. This role requires alignment to Denmark’s time zone.

Qualificações

• Strong experience building and operating data pipelines in AWS.
• Experience with data warehouses and data lake management.
• Ability to collaborate with teams on data models.

Conhecimentos

SQL skills

Python development

AWS Glue

Amazon Athena

Apache Iceberg

Understanding of data lakes

Ferramentas

AWS Services

Apache Flink

Kafka

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