Snowflake

• AWS Data Architect with strong experience in AI. Onsite in Baltimore MD Skills
• Amazon Redshift
• Amazon Web Services
• Big Data
• Data Architecture
• Data Integration
• Data Governance
• Data Management
• Data Analysis
• Data Security
• Data Modeling
• Solution Architecture
• Snowflake
• Amazon Redshift
• Amazon Web Services
• Big Data
• Data Architecture
• Data Integration
• Data Governance
• Data Management
• Data Analysis
• Data Security
• Data Modeling
• Solution Architecture
• Snowflake
• SummaryONSITE Interview
• and Onsite Role in

MDJob Description:

• 14+ years of overall IT experience with 6+ years in solution architecture, system design, and data management.
• Proven experience as a Data Architect, focusing on designing and implementing data solutions in AWS cloud environments.
• Extensive knowledge of Snowflake, AWS cloud services, data lake architecture, and big data technologies.
• Strong understanding of data modeling principles, governance, and security practices.
• Demonstrated expertise in designing data integration solutions and optimizing data processing performance.
• Excellent analytical and problem-solving skills, with the ability to make data-driven decisions.
• Leadership skills to guide and mentor junior data architects and collaborate with cross-functional teams.
• AWS certifications, such as AWS Certified Solutions Architect, AWS Certified Data Analytics
• Specialty, or AWS Certified Big Data
• Specialty, are highly desirable.
• Strong communication and presentation skills to effectively convey complex technical concepts to non-technical stakeholders.
• Join our team as a Senior Data Architect, and be at the forefront of architecting our AWS Cloud-based Lake House to enable data-driven innovation and business success!

Roles and Responsibilities:

• Data Architecture Design:

  Develop and maintain a robust data architecture strategy for the AWS Cloud-based Lake House, encompassing data modeling, data storage, data processing, and data integration across various AWS services, such as S3, Glue, Athena, and Redshift.

• Cloud Data Governance:

  Define and enforce data governance principles, standards, and best practices to ensure data quality, security, and compliance with relevant regulations.

• Data Integration:

  Design and implement efficient data integration processes, enabling seamless data flow between diverse data sources and the data lake infrastructure.

• Performance Optimization:

  Collaborate with data engineers and technical teams to optimize the performance and scalability of the data lake architecture, ensuring high availability and low latency for data access and processing.

• Metadata Management:

  Implement metadata management solutions to enhance data discoverability, lineage, and cataloging within the data lake house.

• Data Security:

  Develop and enforce security measures to protect sensitive data, adhering to industry best practices and AWS security standards.

• Collaboration and Leadership:

  Work closely with cross-functional teams, including data analysts, data scientists, and data engineers, to understand their data requirements and provide technical guidance on data-related initiatives.

• Data Architecture Documentation:

  Maintain comprehensive documentation of the data architecture, including architectural diagrams, design specifications, and data flow processes.

• Technology Evaluation:

  Stay informed about the latest AWS services and data-related technologies, assessing their potential value and recommending their adoption as appropriate.

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Continuous Improvement:

Continuously evaluate the effectiveness of the data architecture, identifying opportunities for enhancement and driving improvements to meet evolving business needs.

Duties:

• Work closely with development teams and customers to design, architect, implement, and support big data solutions.
• Provide design and development of cloud based solutions and is responsible for technical design and implementation of the architecture.

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