Data Platform Engineer (AWS & Data Pipelines)
New
Remote — within LATAM with ET ±1 hour, ET ±1 hourContractSenior
Salary not disclosed
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Job Details
- Languages
- English
- Required Skills
- AWSDockerPythonSQLApache AirflowKubernetesSparkRedshift
Requirements
- Strong professional experience with Python and SQL
- Hands-on experience with AWS, specifically Redshift, EMR and ECS. AWS experience is mandatory (other cloud providers are not considered equivalent for this role)
- Proven experience building and operating both streaming and batch data pipelines
- Professional experience with Apache Airflow, Docker and Kubernetes
- Ability to translate high-level system designs into actionable technical tasks and realistic estimates
- Comfortable working in dynamic and fast-paced environments and in distributed teams
- Strong interest in automation and monitoring
- Strong hands-on experience with Apache Spark
- Senior-level profile with strong autonomy, communication skills and ability to work effectively in distributed teams
- Proven ability to transfer knowledge and support ownership handovers
- Fluent or professional working proficiency in English (both written and spoken)
Responsibilities
- Design, build, maintain and primarily operate scalable streaming and batch data pipelines, with a strong focus on maintenance, monitoring, troubleshooting and continuous improvement of existing pipelines
- Work with AWS services, including Redshift, EMR and ECS, to support data processing and analytics workloads
- Develop and maintain data workflows using Python and SQL
- Orchestrate and monitor pipelines using Apache Airflow
- Build and deploy containerized applications using Docker and Kubernetes
- Break down high-level system designs into well-defined, deliverable tasks with realistic estimates
- Collaborate with cross-functional teams in a fast-paced and distributed environment across the US and Europe
- Drive automation, observability and monitoring to improve reliability, performance and operational efficiency
- Support knowledge transfer and ownership handover as part of the planned transition to the consuming team
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