Data Engineer

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

Resumo da oferta

A technology firm is seeking an experienced Data / ETL Engineer to build and operate data pipelines in AWS. Expertise in SQL and Python is crucial for processing and optimizing data workflows. Familiarity with AWS Glue and Amazon Athena will be vital, along with experience in managing data lakes. The role requires collaboration with various stakeholders to ensure effective data ingestion patterns. Candidates must be willing to work in the Denmark time zone.

Qualificações

• Strong experience in building and operating data pipelines in AWS.
• Hands-on experience with Amazon Athena for querying data.
• Experience with AWS Glue, including Data Catalog and crawlers.

Responsabilidades

• Develop and implement data pipelines on AWS.
• Collaborate with teams on data models and ingestion patterns.
• Optimize data processing workflows using SQL and Python.

Conhecimentos

SQL skills

Python development

Amazon Athena

AWS Glue

Apache Iceberg

AWS 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