Data Engineer

Emagine - Portugal; Teletrabalho; BRL 322.000 - 430.000; Tempo integral

Resumo da oferta

A leading data solutions firm is seeking a Data / ETL Engineer with strong experience in building and operating data pipelines within AWS. The ideal candidate will possess strong SQL and Python development skills, hands-on experience with AWS Glue and Amazon Athena, and a solid understanding of relational databases. The role involves contributing to modern data architectures and working closely with cross-functional teams within the Denmark time zone.

Qualificações

• Solid understanding of relational databases, with strong SQL skills.
• Strong Python development skills for data processing and ETL.
• Hands-on experience with Amazon Athena for querying data.

Conhecimentos

SQL skills

Python

Amazon Athena

AWS Glue

Apache Iceberg

AWS data services knowledge

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