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A leading company in the transportation and logistics sector is seeking a seasoned Data Engineer to spearhead data streaming solutions and maintain data pipelines. This role demands a strong background in data engineering with a focus on security and compliance, offering the chance to work remotely and enjoy a competitive benefits package.
Employer Industry: Transportation and Logistics
Why consider this job opportunity:
- Access to a comprehensive and competitive benefits package, including an industry-leading 401(k) and renowned Railroad Retirement program
- Robust health care options for you and your dependents, including medical, dental, vision, and mental health support
- Annual bonus through an Incentive Compensation Program
- Generous leave/time off policies to promote work-life balance
- Opportunity to work remotely, providing flexibility in your work environment
- Chance to make a significant impact on the transportation of essential products and materials
What to Expect (Job Responsibilities):
- Spearhead the design and implementation of advanced data streaming solutions for real-time data processing
- Architect and maintain resilient data pipelines to ensure data integrity and reliability
- Oversee the management of data marts to meet advanced business intelligence and analytics needs
- Champion data security measures and ensure compliance with industry standards
- Mentor and coach other Data Engineers to strengthen the data engineering team
What is Required (Qualifications):
- MS degree in Computer Science, Information Technology, or a related field; Ph.D. is a plus
- 12+ years of experience in building enterprise data engineering solutions
- Proficiency in programming languages such as Python, R, SQL, and Java
- Expertise in data engineering, focusing on data streaming, data pipelines, and data orchestration tools
- Strong knowledge of database management systems and modern lakehouse technologies
How to Stand Out (Preferred Qualifications):
- Experience in Rail, Shipping, Airline, Logistics, Warehousing, Supply Chain, or other Transportation industries
- Experience working in an Agile environment (Scrum, Kanban, SAFe)
- Knowledge of geospatial data transformation and spatial libraries
- Expertise with MLOps tools like MLflow, Kubeflow, or similar
- Experience in Model Deployment, Model Automation, and Model Monitoring
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