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.
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.
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.
