Cloud Data Solutions Architect
4 days ago
The PBT Group is seeking an experienced Cloud Data Solutions Architect to join our team. In this role, you will be responsible for designing, implementing, and optimizing data pipelines and solutions using AWS and Snowflake.
Key Responsibilities:
- Data Pipeline Design
You will design scalable data pipelines using AWS services (e.g., S3, Glue, Lambda, Redshift) and Snowflake.
Data Storage and Transformation
Implement best practices for data storage, transformation, and optimization in a cloud environment.
Business Intelligence and Analytics
Develop data models to support business intelligence and analytics needs.
Data Integrity and Quality
Ensure data integrity, consistency, and reliability through data validation and quality assurance processes.
Performance Optimization
Optimize data performance and cost efficiency in Snowflake and AWS.
Cross-Functional Collaboration
Collaborate with cross-functional teams to define data architecture and infrastructure requirements.
Automation and Monitoring
Automate data workflows and monitor performance for continuous improvements.
Troubleshooting and Resolution
Troubleshoot and resolve data-related issues.
Requirements:
- Bachelor's degree in Computer Science, Information Systems, or a related field.
- 5+ years of experience in Data Engineering.
- Strong proficiency in AWS cloud services, particularly S3, Glue, Lambda, Redshift, and IAM.
- Hands-on experience with Snowflake, including data warehousing concepts, performance tuning, and optimization.
- Expertise in SQL for data modeling, transformation, and querying.
- Experience with ETL/ELT processes and tools.
- Understanding of data governance, security, and compliance in a cloud environment.
- Proficiency in Python or another scripting language for automation.
Preferred Skills & Experience:
- Experience with data orchestration tools like Apache Airflow.
- Knowledge of DevOps practices and CI/CD pipelines for data workflows.
- Familiarity with Big Data technologies such as Spark or Kafka.
- Exposure to machine learning workflows and MLOps.
- Experience in financial, banking, or insurance sectors.
Key Competencies:
- Strong analytical and problem-solving skills.
- Excellent communication and interpersonal skills.
- Ability to work independently and collaboratively within a team.
- Detail-oriented with a strong focus on data quality and integrity.
- Ability to adapt to a fast-paced and evolving technology landscape.
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