Overview
Remote
$50 - $60
Full Time
Skills
Big Data
Cloud Computing
Collaboration
Communication
Conflict Resolution
Continuous Delivery
Continuous Integration
Data Engineering
Data Modeling
Data Processing
Databricks
Disaster Recovery
Extract
Transform
Load
High Availability
Job Details
Job Summary:
We are urgently seeking a skilled Solution Architect with a strong background in Data Engineering to join our team. The ideal candidate will have hands-on experience in Databricks, Azure, and PySpark, along with a deep understanding of Disaster Recovery planning and Data Engineering principles.
Key Responsibilities:
- Design and architect scalable and secure data solutions using Databricks and Azure.
- Develop and maintain data pipelines using PySpark and other data engineering tools.
- Ensure robust disaster recovery and high availability strategies are in place for critical data systems.
- Collaborate with stakeholders to gather requirements and translate them into technical solutions.
- Evaluate and recommend tools and technologies to enhance data processing workflows.
- Provide technical leadership and mentoring to junior data engineers.
Required Skills:
- Proven experience as a Solution Architect or similar role in data engineering.
- Expertise in Databricks and Azure cloud platforms.
- Proficient in PySpark for data processing and transformation.
- Solid understanding of Disaster Recovery concepts and implementation strategies.
- Strong foundation in data engineering, data modeling, and ETL processes.
- Excellent problem-solving and communication skills.
Preferred Qualifications:
- Azure certification (e.g., Azure Data Engineer, Azure Solutions Architect) is a plus.
- Experience with CI/CD and data pipeline automation.
- Familiarity with big data tools and ecosystem.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.