Remote

Main responsabilities

• Design, build and maintain distributed data pipelines using Airflow, DBT, and modern orchestration frameworks

• Develop and optimize large‑scale data processing workflows using Spark, Flink, or similar distributed engines

• Implement and maintain AWS data services including Glue, EMR, Redshift, Athena, S3, Lambda, and Kinesis

• Apply strong SQL and data modelling skills (dimensional, normalized, lakehouse) to support analytics and data products

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or CircleCI

• Provision and manage cloud infrastructure using Infrastructure as Code (CDK, CloudFormation)

• Implement streaming and event‑driven architectures using Kafka, Kinesis, Flink, or Pub/Sub

• Ensure observability and reliability of data platforms using Grafana, CloudWatch, and modern monitoring practices

• Collaborate with DevOps, platform engineering, and analytics teams to ensure high‑quality data delivery

• Contribute to architectural decisions, documentation, and continuous improvement of data engineering standards

• 5+ years of experience in Data Engineering

• Advanced AWS expertise: Glue · EMR · Redshift · Athena · S3 · Lambda · Kinesis

• Distributed processing frameworks: Spark, Flink ou similares

• Strong proficiency in Python, with working knowledge of Scala, Java ou Go

• Hands‑on experience with Airflow e DBT

• Data modelling expertise: dimensional, normalised e lakehouse

• CI/CD pipelines: GitHub Actions, GitLab CI, Jenkins, CircleCI

• Infrastructure as Code: CloudFormation, CDK

• Streaming / event‑driven architecture: Kafka, Kinesis, Flink, Pub/Sub

• Observability: Grafana, CloudWatch

• Experience with data warehouse platforms: Redshift, Snowflake