Data Engineer

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

Resumo da oferta

A leading technology firm is seeking a Data / ETL Engineer with expertise in building and operating data pipelines within AWS. The ideal candidate will have strong SQL capabilities, solid Python development skills, and hands-on experience with Amazon Athena and AWS Glue. The role requires familiarity with modern data lake architectures and the ability to collaborate with engineers and analysts. This position is remote, but the candidate must work in the Denmark time zone.

Qualificações

• Strong experience with data pipelines in AWS.
• Solid understanding of relational databases.
• Experience with AWS Glue and Glue Data Catalog.

Conhecimentos

SQL skills

Python development

AWS Glue

Amazon Athena

Apache Iceberg

Streaming data pipelines

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