GEN -Senior Data Architect

3 weeks ago


Snowflake, United States QA Minds Full time

Required knowledge, skills and abilities:

Required knowledge, skills and abilities:

- Degree in business, computer science, statistics, applied mathematics or other quantitative field - 10+ years of professional experience creating and supporting enterprise data models and data architecture solutions - 5+ years working with large, global teams - Marketing and Engagement data architecture experience - A proven track record driving innovation and company growth - Expertise in enterprise architecture frameworks, data modeling standards (i.e., conceptual, logical, physical), and metadata management. - Extensive experience with enterprise data ecosystems within a cloud environment (AWS/Azure) - Extensive experience creating and supporting an enterprise data warehouse, master data management & data lake - Experience with modern distributed data technologies (Glue, Athena, Kinesis, Snowflake), relational database systems (PostgreSQL, MySQL) - Experience working within a Snowflake environment - Exceptional critical thinking and analytical skills, with the ability to quickly understand complex systems and data - Experience working within an AWS environment and AWS technologies - Experience designing models to be leveraged for AI, BI, and ML purposes - Demonstrated ability to manage and prioritize workload and roadmaps - Excellent written and verbal communication skills, including the ability to effectively communicate with both technical and non-technical teams - Excellent communication and facilitation skills, with the ability to influence outcomes without a formal position of authority - Self-starter, highly motivated, passionate, enthusiastic and a "can do" attitude - Experience working in an Agile environment Tasks:

Tasks:

- Lead the technical delivery of data architecture deliverables for the organization - Work in tandem with Application Development, Data Engineering, Data Management and Business Intelligence teams to meet business objectives - Support delivery teams to ensure new projects align to established business and technology architecture and standards - Manage, version and extend current enterprise data models (both operational and dimensional) and related metadata - Support the enterprise data governance, data quality and master data management practices across the organization - Provide technical expertise to create a scalable and rich enterprise data ecosystem - Be a technical champion to support continuous improvement of our data architectural practices - Design the future state of data architecture for the organization - Collaboratively work with other technology teams (application, data, security) to ensure business context and priorities are taken into account when technology decisions are made

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