Data Engineer

Company Overview

Daimler Truck is a prominent player in the automotive industry, particularly within the Data & AI department, focusing on developing world-class artificial intelligence platforms across various cloud environments, such as AWS and Azure. The company emphasizes innovation and collaboration to deliver cutting-edge analytics solutions, dashboards, machine learning models, and generative AI solutions on a global scale.

Job Summary

The Data Engineer will play a critical role in designing, developing, and maintaining scalable data pipelines that support the analytics needs of the organization. This position is key to ensuring the quality, integrity, and security of data used in building analytical solutions and AI applications, directly contributing to the success of the Data & AI initiatives.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Snowflake and other cloud-based tools.
• Implement data ingestion, transformation, and integration processes from various sources (e.g., APIs, flat files, databases).
• Optimize Snowflake performance through clustering, partitioning, and query tuning.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements.
• Ensure data quality, integrity, and security across all data pipelines and storage.
• Develop and maintain documentation related to data architecture, processes, and best practices.
• Monitor and troubleshoot data pipeline issues and ensure timely resolution.
• Demonstrate working experience with tools like medallion architecture, Matillion, DBT models, and SNP Glu.
• Possess data modeling experience and exposure to medallion architecture.

Qualifications

• Bachelor’s degree or Master's degree in Computer Science, Information Systems, or a related field.
• 4-5 years of experience in data engineering or a similar role.
• Strong hands-on experience with Snowflake (data modeling, performance tuning, SnowSQL, etc.).
• Proficiency in SQL and experience with scripting languages like Python or Shell.
• Experience with ETL/ELT tools such as dbt, Apache Airflow, Informatica, or Talend.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and services like S3, Lambda, or Data Factory.
• Understanding of data warehousing concepts and best practices.
• Excellent communication skills and a willingness to reskill, adapt, and build strong stakeholder relationships.
• An active team member, willing to go the extra mile and bring innovation to the work.

Preferred Skills

• Experience with additional cloud services and tools is a plus.
• Familiarity with advanced data modeling techniques and methodologies.

Experience

• A minimum of 4-5 years of experience in data engineering or related fields.

Environment

• The typical work environment is adaptable with options for remote working and flexible working models to accommodate individual life phases.

Salary

• Salary details are not specified.

Growth Opportunities

• Opportunities for continuous professional development are available through the company's Learning Academy and free access to LinkedIn Learning.

Benefits

• Attractive compensation package.
• Company pension plan.
• Health offers.
• Individual development opportunities.
• Two additional individual benefits tailored to employee needs.