Solutions Architect, Data Engineering

Job Summary

The Enterprise Data Architect is the leader and subject matter expert that will define, implement, and govern the Information and Data Architecture Strategy for WWE, specifically on designing and implementing the flow, transformation, storage, and visualization of consumer data.  This role will be a key thought leader for evaluating new technologies and solutions, and will partner with Data Analytics and other technology teams across WWE. Our environment is dynamic, fast-paced, and lots of fun.

Key Responsibilities:

• In depth knowledge in Big Data solutions and Hadoop ecosystem to evaluate, recommend, and implement technologies for data ingestion, ETL, storage, and reporting
• Able to design data lake architecture as a centralized data hub to deliver data on demand to manage data for accuracy, currency and usage
• Develop standards for naming, describing, governing, managing, modeling, storing, cleansing, transforming, searching, and delivering all consumer data within WWE (which includes methodologies, tools, governance, and conventions)
• Provide architecture guidance, solution architecture, technology leadership, best practices, detailed design, and lead development efforts
• Work with the Data Analytics team (i.e., Data Scientists) to translate business requirements to functional requirements and implement realistic technology solutions for the same
• Understand how the data relates to the current operations and the effects that any future process changes will have on the use of data in the organization
• Work with team members and other technology groups to ensure all systems are scalable, optimized for performance, have full DR redundancy, and are secure.
• Build COE for data information life cycle management, governance, lineage, and quality
• Manage custom development of data integration platform for Big Data platform

Qualifications:

• 10+ years in enterprise data architecture
• 8+ years of experience architecting and supporting high-performance, highly-available, and scalable Information Management solutions
• 10+ years of experience with implementing data reporting, integration, and visualization tools (i.e., Cognos, Informatica, Python Spark, Tableau, etc.)
• Proven expertise in Relational and Dimensional Data Modeling
• Strong understanding of cloud architecture, specifically AWS, as it relates to data processing (i.e., EC2, S3, Redshift, etc.)
• AWS certification preferred
• In depth knowledge in Big Data solutions and Hadoop ecosystem
• Understand PII standards, processes, and security protocols
• Familiarity with Data Anonymization concepts and technologies preferred
• Experience leading and architecting enterprise wide initiatives, specifically system integration, data warehouse build, data mart build, data lakes, etc. for a large enterprise
• Able to confidently express the benefits and constraints of technology solutions to technology partners, stakeholders, team members, and senior levels of management
• Experience implementing and supporting Operational Data Stores, Data Warehouses, and Data Marts and Data integration platforms.
• Experience leading Information Management related initiatives (system integration, data warehouse build, data mart build, or similar)
• Experience with physical, logical, and conceptual data modeling
• Basic ability to manage, implement, and write ETL scripts (experience with Python & Spark preferred
• Willing and able to work flexible hours and be “on-call” as needed
• Relevant college degree in Computer Science (or related technical field) preferred