Data Engineer

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

Resumo da oferta

A leading data solutions company is looking for experienced Data/ETL Engineers in Brazil, specifically in Rio Grande do Sul, Sapiranga. The role requires strong expertise in building AWS data pipelines, with skills in SQL, Python, AWS Glue, and Amazon Athena. Ideal candidates should also have familiarity with technologies like Apache Flink and Kafka. The position involves collaborating with engineers and stakeholders in the Denmark time zone.

Qualificações

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

Conhecimentos

SQL

Python

Data processing

AWS Glue

Amazon Athena

Apache Iceberg

AWS data services

Ferramentas

Apache Flink

Kafka

Descrição da oferta de emprego

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