Data Engineer [T500-29046]
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Key skills for this role
Role Overview
The Data Engineer will build and optimize data infrastructure supporting analytics and AI initiatives.
The role enables analysts, data scientists, and stakeholders to use trusted, accessible, and actionable data.
The company uses modern tooling and provides training, mentoring, and opportunities to shape engineering practices.
Key Skills for This Role
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About Stolt-Nielsen
Stolt-Nielsen is a global provider in bulk-liquid and chemical logistics, transportation, and storage.
The Digital Innovation Centre develops systems and digital capabilities for the logistics business.
Role overview
The Data Engineer will build and optimize data infrastructure supporting analytics and AI initiatives.
The role enables analysts, data scientists, and stakeholders to use trusted, accessible, and actionable data.
The company uses modern tooling and provides training, mentoring, and opportunities to shape engineering practices.
What you will do
- Design and maintain Databricks pipelines using PySpark and Delta Lake.
- Build ETL and ELT processes for APIs, databases, files, and cloud systems.
- Optimize data models and storage for analytics, machine learning, and BI reporting.
- Write SQL queries, views, and stored procedures for transformation and analysis.
- Translate business needs into technical solutions with cross-functional teams.
- Implement data quality, governance, and security standards.
- Monitor and troubleshoot workflows for performance, reliability, and cost efficiency.
- Keep current with data engineering and cloud-native architecture best practices.
Required qualifications
- A bachelor's or master's degree in computer science or a related field is required.
- At least 2 years of hands-on experience as a Data Engineer, ETL Developer, or similar is required.
- Strong Python proficiency, including PySpark and pandas, is required.
- Excellent SQL skills for manipulation, tuning, and debugging are required.
- Hands-on Databricks experience with workspaces, notebooks, jobs, clusters, and Unity Catalog is required.
- Understanding of warehousing, data modeling, distributed processing, dimensional modeling, and medallion architectures is required.
- Azure PaaS experience for data and storage is required.
- Analytical ability, attention to detail, communication, and cross-functional collaboration are required.
- Experience with CI/CD, automated testing, and Agile delivery is required.
Must-have skills
- Databricks, PySpark, Delta Lake, Jobs, Workflows, and Unity Catalog or metadata experience.
- Python skills for data processing and automation.
- Advanced SQL querying and performance tuning.
- Data pipeline orchestration, version control, CI/CD, and data modeling experience.
Nice-to-have skills
- Familiarity with dbt or modern data stack tools.
- Knowledge of governance, cataloging, and access control tools such as Unity Catalog or Purview.
- Exposure to machine learning workflows and model data preparation.
- Experience with Databricks performance tuning and cost optimization.
- Background with ERP financial modules.
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