Data Engineer

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

Resumo da oferta

A technology firm is seeking a Data / ETL Engineer skilled in building and operating data pipelines in AWS. The ideal candidate will have strong SQL skills, proficiency in Python for data processing, and hands-on experience with Amazon Athena and AWS Glue. Familiarity with streaming data pipelines and modern data lake architectures is preferred. This role requires collaboration with engineers and analysts, and the candidate must work in the Denmark time zone.

Qualificações

• Experience with Microsoft SQL Server preferred.
• Strong experience with building data pipelines in AWS.
• Familiarity with streaming data pipelines is a plus.

Responsabilidades

• Build and operate data pipelines in AWS.
• Utilize SQL for managing relational databases.
• Collaborate on data models and ingestion patterns.

Conhecimentos

SQL skills

Python development

Amazon Athena

AWS Glue

Apache Iceberg

AWS data services

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