Data Architect

​About Goosehead 

Since 2003, Goosehead Insurance has been disrupting the insurance industry by giving clients the power of choice, utilizing a smarter marketing approach, and delivering world-class service. This is all powered by our focus on hiring and retaining extraordinary people. Our clients trust us with their most valuable possessions, so we’re more than just a bit selective when it comes to hiring new team members. 

Job Summary 

In this role you will be responsible for ensuring that the company's data ecosystem is robust, secure, and capable of supporting data-driven ambitions. Design, create, deploy, and manage an organization's data architecture. Define how the data will be stored, consumed, integrated, and managed by different data entities and IT systems, as well as any applications using or processing data. 

Principal Duties and Responsibilities  

• Define and implement the enterprise data strategy aligned with long-term business objectives. 

• Design scalable, secure and flexible data architecture enabling data-driven decision-making. 

• Collaborate with executive leadership and bridge cross-functional teams to align data initiatives with business needs. 

• Architect and deploy end-to-end data solutions, including data lakes, data warehouses, lakehouses, integration pipelines, and modeling frameworks. 

• Create and optimize data ingestion, transformation, and integration processes using industry-standard ETL/ELT tools to support both real-time and batch data flows. 

• Oversee enterprise-wide data integration, ensuring seamless interoperability across systems, applications, and departments. 

• Establish and enforce data governance policies, ensuring data integrity, security, privacy, and compliance with regulatory standards. 

• Evaluate, select, and implement modern data platforms and technologies, with a strong focus on cloud-native solutions (e.g. Azure, Databricks, Snowflake). 

• Utilize programming languages such as Python and SQL to design and implement scalable data pipelines. 

• Help implement DevOps and DataOps best practices including CI/CD pipelines, version control, code reviews, and automated testing for data infrastructure and transformation workflows. 

• Stay current with industry trends, emerging technologies in data architecture, cloud, and artificial intelligence. 

• Work closely with IT teams, data engineers, data scientists, and analysts to ensure consistency and alignment. 

• Provide technical leadership and mentorship, fostering a culture of innovation, collaboration, and continuous learning within the data team. 

Experience and Education 

• Bachelor’s degree in Computer Science, Information Systems, Data Science, or related field required. Master’s degree or advanced certifications preferred. 

• Over 5+ years of