Data Engineer

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

Resumo da oferta

A technology firm is seeking a Data / ETL Engineer with strong AWS experience. The ideal candidate will build and operate data pipelines, focusing on relational databases and SQL. Key skills include Python development and AWS Glue, with familiarity in Apache Flink and Kafka being a plus. This role involves collaboration with analysts and stakeholders. Working hours will align with the Denmark time zone.

Qualificações

• Strong experience building and operating data pipelines in AWS.
• Solid understanding of relational databases with strong SQL skills.
• Hands-on experience with Amazon Athena for querying data in data lakes.

Responsabilidades

• Develop and maintain data pipelines in AWS.
• Collaborate with teams around data models and ingestion patterns.
• Ensure operational best practices for data processing.

Conhecimentos

Relational databases

SQL

Python development

AWS Glue

Amazon Athena

Apache Iceberg

AWS services

Ferramentas

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