44 applicants

Company

Signet Jewelers · 3 days ago

Cloud Data Architect

United States

Full-time

Remote

Senior Level

$116K/yr - $180K/yr

5+ years exp

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Hiring Manager

Amanda King

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Responsibilities

Architectural Guidance: Contribute recommendations and roadmaps for future architecture, actively shaping comprehensive and strategic plans communicated to business decision-makers, with a focus on cloud data platform engineering.

Platform Standardization: Play a key role in maintaining and updating all strategic architecture plans and documentation, ensuring alignment with evolving business goals, and integrating data engineering principles.

Enterprise Architecture Activities: Participate in technical and architecture activities to ensure that decision making considers the entire enterprise's goals and needs. This includes but is not limited to Architectural Review Board (ARB) reviews and follow-up monitoring of project design and delivery activities.

Proof of Concepting: Build POCs that can be evaluated by others and used to determine the viability of a solution.

Peer Mentorship: Functioning as a peer leader, serve as a mentor to colleagues, sharing knowledge and expertise in the realm of data platform architecture, fostering a collaborative learning environment that enhances the professional development of team members.

Innovative Ideation: Proven ability as a Cloud Data Architect to consistently provide innovative ideas, leveraging cutting-edge technologies and emerging trends to enhance the architecture of cloud data platforms, driving forward-thinking solutions for data management and analytics.

Data Platform Engineering: Actively engage in the development of the enterprise data platform.

Optimize AWS Data Platform Costs: Actively contribute to the optimization of costs within the AWS data platform, leveraging efficient resource management strategies and promoting awareness among peers about cost-effective practices, ensuring the platform operates in a financially prudent manner.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

AWS RedShiftData Pipeline DevelopmentETL ProcessesPython for Data EngineeringData WarehousingServerless ComputingData SecurityMonitoringOptimizationDocumentation

Required

College degree in Computer Science, Data Engineering, Computer Engineering, or related field of study.

5 years or more of experience in a relevant technology field.

Proficiency in managing and optimizing AWS RedShift databases.

Hands-on experience in designing, building, and optimizing data pipelines on AWS using services like AWS Glue, Amazon EMR, or Apache Spark.

Experience in architecting and implementing data warehousing solutions on AWS, leveraging services like Amazon Redshift for scalable and high-performance analytics.

Expertise in designing and implementing Extract, Transform, Load (ETL) processes, ensuring the seamless flow of data from source to destination within the AWS ecosystem.

Essential expertise in Python programming within the context of data engineering, including the ability to develop and optimize data pipelines, conduct data transformations, and implement data processing tasks efficiently and effectively.

Familiarity with serverless computing on AWS, utilizing services like AWS Lambda for efficient and cost-effective data processing.

Knowledge of implementing robust data security measures on AWS, including encryption, access controls, and compliance with data protection regulations.

Proven ability to implement monitoring solutions and optimize data engineering workflows on AWS, ensuring performance, scalability, and cost-effectiveness.

Experience in collaborating with cross-functional teams and documenting data engineering processes, ensuring clear communication and knowledge transfer within the organization.

Demonstrated capability in identifying and resolving data engineering challenges, including troubleshooting issues and implementing effective solutions in an AWS cloud environment.

A commitment to staying updated on the latest AWS cloud data engineering trends, tools, and best practices through continuous learning and professional development.