DBT Architect

Mandatory Skills AWS Data Services, DBT Core, Airflow, Spark, Power BI, Data Lake, GIT, Architecture & Design, SQL
Secondary Skills Release management, Project Management, Azure Data Services

Job Summary We are seeking a highly skilled Data Build Tool Architect to join our team. The ideal candidate will have extensive experience in designing, implementing, and managing data build tools and frameworks. This role involves leading the architecture and development of scalable data solutions to support our data-driven initiatives.
Key Responsibilities
Architect and Design Data Solutions Lead the design and architecture of data build tools and frameworks to support data integration, transformation, and loading processes.
Cloud Integration Integrate data build tools with cloud platforms, primarily AWS, to ensure seamless data processing and storage.
Performance Optimization Optimize data build processes for performance, scalability, and cost-efficiency.
Agile Collaboration: Work closely with data engineers, data anayst, and other stakeholders to understand data requirements and deliver robust solutions.
Automation Implement automation for data build processes to enhance efficiency and reduce manual intervention.
Security and Compliance Ensure all data build tools and processes adhere to security and compliance standards.
Troubleshooting Identify and resolve issues related to data build tools and processes.
Qualifications
Experience Minimum of 5 years of experience in data engineering, with a focus on data build tools and architecture.
Technical Skills Expertise in DBT (data build tool), cloud platforms (AWS), and programming languages (Python, SQL).
Education Bachelors or Masters degree in Computer Science, Information Technology, or a related field.
Certifications AWS Certified Solutions Architect or AWS Certified Data Analytics is a plus.
Soft Skills Strong problem-solving skills, excellent communication, and the ability to lead and collaborate with cross functional teams.
Preferred Qualifications
Experience with big data technologies like Hadoop, Spark, or Kafka.
Familiarity with containerization and orchestration tools like Podman, Rancher and Kubernetes.
Knowledge of data warehousing and tools Data integration, Data transformation, Orchestration, Reporting