Senior Data Engineer (B2B)

Quick Facts

• Role: Senior Data Engineer (B2B)
• Focus: Data Engineering / Data Science for logistics
• Stack: Snowflake, SQL, Python, Airflow, CI/CD, Infrastructure-as-Code
• Collaboration model: B2B contract
• Work setup: Hybrid (Wrocław) or 100% remote

Description

Join the data team responsible for building the data architecture for logistics, delivering pipelines, infrastructure, and tools that enable data-driven strategic decisions. You will design and evolve reusable data engineering solutions—ideally with Snowflake—support early integration of new technologies, and help deliver reliable production pipelines with CI/CD and Infrastructure-as-Code. You will collaborate closely with Data Science experts and other stakeholders.

Responsibilities

• Operate and further develop data pipelines and infrastructure for Data Engineering and Data Science projects in logistics
• Design reusable solutions and templates for self-service adoption by less technical teams
• Support early integration of new technologies in the organization’s tech stack
• Design reliable data pipelines and CI/CD flows; support their deployment to production
• Implement Infrastructure-as-Code and automated deployment pipelines with both technical and strategic considerations
• Collaborate cross-functionally and support ongoing development of documentation and coding standards

Requirements

• German or English: fluent (minimum B2/C1); Polish: C1
• Multi-year experience with data pipelines and cloud data warehouses (preferably Snowflake), including SQL, data modeling, and access-rights concepts
• Deep knowledge of Infrastructure-as-Code and CI/CD (preferably OpenTofu/Terraform and GitLab CI/CD)
• Practical Data Engineering experience with Python, Snowflake, Airflow, and automated deployment pipelines
• Preferred experience operating data products (monitoring/alerting, automated dependency management such as Renovate)
• Proactive, responsible, and strong communication/collaboration skills
• Completed degree in Computer Science, Mathematics, Engineering, or Natural Sciences

Benefits

• Partner-like collaboration with autonomy and a dialog-focused product-team culture
• Flexible cooperation model with no rigid working hours; trust and outcomes-focused approach
• Structured onboarding plan delivered in advance