Data Architect

Advance Local is looking for a Data Architect to lead the design and implementation of enterprise-level data solutions within our modern cloud data platform. This role combines deep technical expertise in analytics engineering with leadership responsibilities to ensure the delivery of well-documented, tested, and  high-quality data assets that enable AI, data products, advanced analytics, and self-service reporting.  You’ll guide strategic data initiatives, mentor a team of analytics engineers, and collaborate with data engineering and business stakeholders to deliver impactful, scalable solutions.

The base salary range is $185,000 - $200,000 per year.

What you’ll be doing:

• Architect and oversee scalable data models, pipelines, and frameworks in Snowflake using dbt, ensuring that they meet quality standards for AI agents, advanced analytics, and self-service reporting.
• Lead the design and governance of analytics-ready data models, ensuring they are well-modeled, performant, and accessible to downstream consumers.
• Drive rapid prototyping of new data products and features, providing technical direction and hand-on guidance when needed.
• Establish and enforce data quality, testing, and documentation standards across all data assets, ensuring reliability and trustworthiness.
• Develop advanced solutions for audience data modeling and identity resolution, supporting personalization and segmentation strategies.
• Partner with Audience Strategy and Insights teams to translate requirements into technical solutions and automation.
• Collaborate with the Lead Data Engineer on data integration patterns and ensure seamless handoffs between raw data ingestion and analytics-ready models.
• Establish data architecture standards and development practices (version control, CI/CD, testing frameworks) that enable team scalability.
• Enable data accessibility and integration solutions that support both technical and non-technical users across the organization.
• Provide technical leadership to a Data Manager and their team of analytics engineers, fostering a culture of best practices, code review, and continuous improvement.

Our ideal candidate will have the following:

• Bachelor’s or master’s degree in computer science, data engineering, information systems, or related field
• Minimum ten years’ experience in data engineering, data analytics engineering, architecture, or related roles, with proven experience leading data teams and managing complex data ecosystems
• Expert level proficiency in dbt and Snowflake with demonstrated ability to build production-grade data models and pipelines
• Strong knowledge of cloud platforms (AWS, Azure, GCP) and data warehousing best practices
• Proficiency in big data technologies (Spark, Hadoop) and streaming frameworks
• Familiarity with data governance, security, and compliance standards
• Experience with audience segmentation, marketing analytics, or customer data platforms
• Knowledge of machine learning pipelines, advanced analytics and AI applications
• Strategic thinking and ability to align data initiatives with business objectives
• Strong communication and stakeholder management skills
• Proven ability to lead cross-functional teams and drive organizational change
• Experience building data solutions that support self-service analytics and data demonstrations