Rate: Depending on experience

Work location: Dearborn, MI (hybrid)

*Must-Have:

- Bachelor’s degree in science, Technology, Engineering, or Mathematics.

- 7 years of experience as a data engineer, with strong proficiency in Azure cloud services, Databricks, and Azure Data Factory

- 3 years of experience with designing and implementing data solutions using Azure Cloud.

- Azure Data Engineering or Databricks Certification.

- Strong knowledge of programming languages such as Python, SQL, or Scala.

- Experience with data modeling, ETL/ELT development, data integration and orchestration techniques

- Experience with designing and developing end-to-end data and analytics solutions leveraging Azure Data Lake, Azure Databricks, and Data Factory

*Nice to Have:

- Experience with designing scalable data analytics architecture to implement advanced analytics solutions, including machine learning and AI, to extract actionable insights from data.

- Additional Azure Certifications like Azure ML, Analytics Specialty, or Azure Solutions Architect

*Responsibilities:
- Lead the design and implementation of complex cloud solutions using Microsoft Azure, focusing on integration with Databricks and Azure Data Factory.
- Develop and maintain scalable and efficient data pipelines and architectures.
- Ensure optimal architecture and performance of applications deployed on Azure.
- Provide expertise in cloud security, ensuring compliance with industry standards and company policies.
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
- Manage the full lifecycle of data and analytics solutions, from requirements gathering to deployment and maintenance.

Other responsibilities:

- Mentor and lead a team of cloud engineers, promoting best practices in cloud computing and continuous learning.
- Conduct system troubleshooting and provide technical support as needed.
- Stay updated with the latest developments in cloud technologies and introduce innovations and improvements to internal systems.