Data Engineer
⚲ Remote
22 680 - 24 360 PLN (B2B)
Wymagania
- Cloud
- Python
- SQL
- ETL
- REST API
- Google cloud platform
- BigQuery
- Kubernetes
- Infrastructure as Code
- Security
- IAM
- VPC
- CD pipelines
- GitHub Actions
Opis stanowiska
O projekcie:
This role is focused on the development and lifecycle management of a specialized, enterprise-grade laboratory and assay data platform. The platform's primary goal is to operationalize and deliver advanced data products associated with analytical, chemical, or biological assays.
As a Cloud Data Engineer, you will join the team responsible for implementing and supporting data products built on top of this platform, which includes building the underlying pipelines and transformations required for stable data delivery. You will work closely with cross-functional product and engineering teams to deploy new features, ensuring strict adherence to strict enterprise cloud security and engineering standards.
Wymagania:
- 5+ years of professional experience as a Data Engineer, Cloud Data Engineer, or a related role.- Strong proficiency in Python and advanced SQL development.- Hands-on experience building robust ETL/ELT workflows and interacting with REST APIs.- Solid expertise in Google Cloud Platform (GCP), specifically focusing on BigQuery (BQ), Dataproc, and GKE (Google Kubernetes Engine).- Proven production experience with Infrastructure as Code using Terraform.- Strong familiarity with enterprise cloud security concepts, specifically IAM and VPC-SC (VPC Service Controls).- Experience setting up automation and CI/CD pipelines using GitHub Actions.- Familiarity with Agile methodologies and collaborative workflows.- Strong communication and interpersonal skills with fluent English (C1 level minimum) and Polish min. B2
Codzienne zadania:
- Implementation & Delivery: Build and support data products utilizing the internal assay data platform, managing data pipelines and transformations necessary for delivering domain-specific data assets.
- Post-Production Support: Provide engineering support for production data products, resolving technical issues and defects raised via ticketing tools in alignment with agreed business priorities.
- Feature Engineering: Develop and deliver new features, components, and enhancements based on requirements provided by product teams, ensuring robust and high-performing solutions.
- Cloud & Security Management: Maintain infrastructure as code and secure data boundaries within a highly regulated, enterprise cloud network.
This role is focused on the development and lifecycle management of a specialized, enterprise-grade laboratory and assay data platform. The platform's primary goal is to operationalize and deliver advanced data products associated with analytical, chemical, or biological assays.
As a Cloud Data Engineer, you will join the team responsible for implementing and supporting data products built on top of this platform, which includes building the underlying pipelines and transformations required for stable data delivery. You will work closely with cross-functional product and engineering teams to deploy new features, ensuring strict adherence to strict enterprise cloud security and engineering standards.
Wymagania:
- 5+ years of professional experience as a Data Engineer, Cloud Data Engineer, or a related role.- Strong proficiency in Python and advanced SQL development.- Hands-on experience building robust ETL/ELT workflows and interacting with REST APIs.- Solid expertise in Google Cloud Platform (GCP), specifically focusing on BigQuery (BQ), Dataproc, and GKE (Google Kubernetes Engine).- Proven production experience with Infrastructure as Code using Terraform.- Strong familiarity with enterprise cloud security concepts, specifically IAM and VPC-SC (VPC Service Controls).- Experience setting up automation and CI/CD pipelines using GitHub Actions.- Familiarity with Agile methodologies and collaborative workflows.- Strong communication and interpersonal skills with fluent English (C1 level minimum) and Polish min. B2
Codzienne zadania:
- Implementation & Delivery: Build and support data products utilizing the internal assay data platform, managing data pipelines and transformations necessary for delivering domain-specific data assets.
- Post-Production Support: Provide engineering support for production data products, resolving technical issues and defects raised via ticketing tools in alignment with agreed business priorities.
- Feature Engineering: Develop and deliver new features, components, and enhancements based on requirements provided by product teams, ensuring robust and high-performing solutions.
- Cloud & Security Management: Maintain infrastructure as code and secure data boundaries within a highly regulated, enterprise cloud network.
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