• Work with clients as a participant in their BigQuery and Looker analytics journey • Understand client needs from an organizational, process, and technological perspective • Lead interactive working sessions and conduct hands-on workshops with client technical teams • Design, implement, and maintain data models in Looker, ETL pipelines, and build actionable dashboards

• Architect, design, and lead the implementation of highly complex, scalable, and resilient data solutions in the cloud, leveraging AWS, Snowflake, dbt, Fivetran, and other modern technologies. • Be the Expert. Quickly build subject matter expertise in a specific business area and data domain. Understand the data flows from creation, ingestion, transformation, and delivery. • Support defining and executing the overarching strategy for the analytics engineering function, including the development and evangelization of data frameworks, standards, and best practices across the organization. • Lead efforts in designing, building, and maintaining a robust, governed, and scalable semantic layer to provide consistent and reliable data access for business intelligence and analytics. • Spearhead the technical vision and roadmap for data quality and governance, establishing frameworks and processes to ensure data integrity and proactively address systemic issues. • Act as a primary technical consultant to senior executives and business stakeholders, translating complex data concepts into actionable insights and strategic recommendations. • Mentor, coach, and develop junior and mid-level analytics engineers, fostering a culture of technical excellence, innovation, and continuous learning within the team. • Set standards for documentation, conduct advanced peer code reviews, and define comprehensive testing strategies for data solutions. • Continuously evaluate and champion new technologies and methodologies to enhance the data and analytics capabilities at Huntress.

• Lead complex product pipeline builds: Design and develop scalable data pipelines supporting cross-domain product launches in Payments, Credit, and Subscriptions, from scoping through delivery • Collaborate cross-functionally: Partner with Product Analysts and Product Managers to define data requirements, while analysts continue owning pipelines alongside you • Build product reporting infrastructure: Create reliable, performant marts and models that power product dashboards and self-service analytics • Design scalable data models: Apply modeling frameworks (one big table, entity tables, Kimball) tailored to product analytics use cases • Optimize and monitor: Maintain pipeline health, optimize query performance, and implement data quality monitoring • Enable the team: Document solutions, establish best practices, and help upskill Product Analysts on pipeline development • Integrate cross-functional data: Work across domain boundaries to unify product data into cohesive reporting structures

• Own the Data Ecosystem: Build and maintain robust data pipelines and ETL processes • Design and manage data warehouses to support advanced analytics, focusing on creating 'Gold Standard' data models • Maintain comprehensive documentation of all data engineering processes • Design and manage data lakes, warehouses, and databases to support advanced analytics and AI workflows • Act as a SQL/Python expert to optimize data pipelines and troubleshoot issues