Cradlepoint - Boise, ID

posted about 2 months ago

Full-time
Boise, ID
Computer and Electronic Product Manufacturing

About the position

The Marketing Database Architect will be responsible for designing, implementing, and maintaining the architecture of our marketing databases. This role is crucial in ensuring that our marketing data is structured, secure, and accessible to support advanced analytics, personalized marketing campaigns, and overall data-driven decision-making. The ideal candidate will have a strong background in database management, data modeling, and marketing technologies. In this position, you will design and develop scalable and efficient database solutions that meet the needs of the marketing department, including data warehouses, data marts, and operational databases. You will create and maintain data models to support marketing analytics, campaign management, customer segmentation, and personalization efforts. Additionally, you will develop and manage processes for integrating data from various sources, including CRM systems, marketing automation platforms, and third-party data providers. Monitoring and optimizing database performance will be a key responsibility, ensuring that queries are efficient and that databases are properly indexed. You will also implement and enforce data security protocols, ensuring compliance with data protection regulations such as GDPR and CCPA. Collaboration with marketing, IT, and analytics teams will be essential to understand business requirements and translate them into technical solutions. Comprehensive documentation of database architectures, data models, and data flows will be maintained as part of your duties. Staying current with emerging trends and technologies in database management, marketing technology, and data analytics will be important to recommend and implement improvements. This role requires a proactive approach to innovation and a commitment to continuous learning in the rapidly evolving field of marketing technology.

Responsibilities

  • Design and develop scalable and efficient database solutions that meet the needs of the marketing department, including data warehouses, data marts, and operational databases.
  • Create and maintain data models to support marketing analytics, campaign management, customer segmentation, and personalization efforts.
  • Develop and manage processes for integrating data from various sources, including CRM systems, marketing automation platforms, and third-party data providers.
  • Monitor and optimize database performance, ensuring that queries are efficient and that databases are properly indexed.
  • Implement and enforce data security protocols, ensuring compliance with data protection regulations such as GDPR and CCPA.
  • Work closely with marketing, IT, and analytics teams to understand business requirements and translate them into technical solutions.
  • Maintain comprehensive documentation of database architectures, data models, and data flows.
  • Stay current with emerging trends and technologies in database management, marketing technology, and data analytics to recommend and implement improvements.

Requirements

  • Bachelor's Degree in Marketing, Engineering, Math, Computer Science, Statistics or other related degrees.
  • Five to seven (5-7) years of experience in data management, marketing operations, or business analyst role.
  • Experience with SQL and NoSQL databases, such as MySQL, PostgreSQL, Snowflake, or similar is essential.
  • Strong understanding of marketing technology stacks, including CRM, marketing automation platforms, and data analytics tools.
  • Proficiency in data integration techniques, ETL processes, and data warehousing.
  • Familiarity with data privacy laws and regulations, including GDPR and CCPA.
  • Excellent problem-solving skills and attention to detail.
  • Strong communication skills, with the ability to convey technical concepts to non-technical stakeholders.
  • Ability to work independently and as part of a team in a fast-paced environment.

Nice-to-haves

  • Experience in cloud-based database solutions, such as Azure, Google Cloud, or AWS.
  • Experience with machine learning and AI-driven data analysis.
  • Experience with Python for data analysis and development.
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