AWS Data Engineer

Job Description

As an AWS Data Engineer at Verisk, you will collaborate with architects, engineers, and business leaders to execute the organization's strategic data architecture vision. This role involves taking ownership of data architecture for global data platform initiatives.

Responsibilities

• Serve as the technical owner for data architecture on global data platform projects.
• Design and develop data flows and data models for systems producing data assets.
• Scale architectural design through data engineering, data governance, and solutions architecture.
• Lead the development of data architecture best practices, standards, design review processes, and repeatable design documents.
• Foster a culture of data architecture fluency and technical enablement.
• Act as a technical thought leader and innovator, integrating new technologies and methodologies.
• Develop and implement quality metrics for data to assess and optimize the data landscape.

Qualifications

• Bachelor's or Master's degree in Computer Science/Engineering or equivalent experience.
• 1-3 years of experience with Python and SQL.
• Hands-on experience with relational, dimensional, and analytic data management tools, including RDBMS, NoSQL platforms, and ETL/data ingestion protocols.
• Experience with data warehouses, data lakes, and enterprise big data platforms in multi-data-center environments, with a focus on energy data sets.
• At least one current AWS or cloud certification and documented thought leadership in data architecture.

Impact

• Experience designing scalable and repeatable data architectures to solve business challenges through innovation.
• Recognized subject matter expert in data architecture, serving as an internal and external thought leader.
• Proven ability to transform data quality through metrics and measured improvements.

Collaboration

• History of mentoring and leading engineering teams to enhance their architecture capabilities.
• Experience influencing technical decisions across various stakeholder levels, including non-technical audiences.
• Ability to foster a culture of data-driven reliability, observability, monitoring, and automation.
• Proven ability to thrive in ambiguous environments and make sound judgment calls to achieve results.

Depth

• Mastery of at least one big data technology and its management principles.
• Proficiency in at least one data engineering-related programming language.
• Mastery of cloud data architecture and large-scale data integration.