Data Architect II - Mobile

As part of the Adrenaline team, you will develop data architectures which will support to depict player evolution year-over-year in AAA titles in a changing technology landscape. You will engage with us and a wider range of team members including game studios, the EA business at all levels, analysts, technology partners, and other teams. You will also look at how to develop and provide high-level subject matter expertise on the analytics platform contributing to the development of the data strategy and supporting investment plans. You will report to Director of Data Architecture.

What you will do:

• Work with Business and technical team members to define use case and associated data models into data solutions and bring them to completion with data engineering and product management .
• Translate strategic requirements into a usable data architecture, which includes data model, associated metadata, data flow, data lifecycle, and taxonomies to guide analytics solution development.
• Develop conceptual, logical, physical, and transformational data models.
• Contribute to the managing, modelling, cleansing, enriching, transforming, integration, backup, retention, archiving and delivery of data.
• Ensure data quality by developing and publishing data standards such as naming conventions, data standards and transformation rules.
• Architect technical roadmaps to address data opportunities or challenges, including data quality, integration, and workflow, and identifying architecture inconsistencies/compliance.
• Ensure completion of tasks, milestones, and components, including functional specifications, design specifications, configurations, quality assurance, implementations, and project reviews
• Conduct requirements mapping, vendor evaluations, technical proof-of-concept projects, use cases and test cases.

Qualifications:

• Bachelor Degree in CS/Statistics/Math or equivalent experience
• 5+ years of work experience with enterprise data warehousing, data management, business intelligence and large-scale data solutions
• Knowledge in Reference Data, Data Quality, Metadata Management
• Experience with Google Cloud Platform's Data Components (GCS, BigQuery, PubSub, Vertex AI)
• knowledge of data privacy practices and laws (internationally)
• Experience in data modelling techniques and documentation.
• Passion to build quality products for massive scale in a collaborative and agile environment, and an excitement to learn