Data Engineer

Role Overview:

As a Data Engineer, you will help to shape the Cargoo’s data engineering strategy and guide the design, architecture, and implementation of scalable data solutions. You will support a team of data engineers, collaborate closely with AI engineers, BI analysts, and business stakeholders, and ensure our data infrastructure supports advanced analytics, machine learning, and real-time decision-making.

You will work with teams across the company to identify data opportunities to drive impact, understand their needs, and help them get the most out of our Data Platform.

Responsibilities:

• Shape and contribute to Cargoo’s data engineering strategy, including the design, architecture, and implementation of scalable data solutions.
• Build, maintain, and evolve the Data Platform to support advanced analytics, machine learning, and real-time decision-making.
• Collaborate closely with AI engineers, BI analysts, and business stakeholders to translate data needs into robust technical solutions.
• Identify data opportunities across the organization and enable teams to extract maximum value from data assets.
• Design and implement ETL/ELT pipelines, including batch and streaming data workflows.
• Develop and maintain data models using dimensional and advanced modeling techniques.
• Support deployment, monitoring, and lifecycle management of data applications.
• Apply DataOps best practices to ensure reliability, scalability, and quality of data pipelines.
• Participate in code reviews and promote high engineering standards.
• Take ownership of projects end-to-end, ensuring timely delivery and measurable impact.

Requirements:

• Solid proficiency in Python (runtime environment, package management) and SQL (DML, DDL).
• Hands-on experience with SQL Server / Azure SQL Server.
• Experience working with cloud platforms, preferably Microsoft Azure.
• Familiarity with the modern data stack, including tools such as dbt and orchestration frameworks (Airflow, Dagster, or similar).
• Strong understanding of ETL/ELT concepts, data architecture, and data modeling.
• Experience with streaming technologies (Kafka or equivalent).
• Experience with Docker and container orchestration technologies.
• Experience deploying and monitoring applications on Kubernetes (K8s).
• Knowledge of application lifecycle management.
• Understanding and application of DataOps practices.
• Strong project management, execution skills, and a clear sense of ownership and accountability.

Why you’ll love it here:  

• Work with a cutting-edge data stack to power real-time, reliable, and beautifully orchestrated data workflows. 
• Turn insights into impact - help shape smarter global logistics solutions. 
• Collaborate with curious, data-driven people who value ideas. 
• Learn, experiment and grow in a culture that supports your ambition. 
• Enjoy Stebby perks or health insurance, snacks and free parking. 
• Be part of a team that celebrates wins together.
• Grow, build and belong with us.