• Lead a high-performing team of cloud ETL and Data Engineering, promoting a culture of innovation, collaboration, and knowledge. • Architect and oversee the development of scalable, cloud-native data pipelines using technologies like Apache Spark and Airflow across AWS, GCP, or Azure. • Collaborate with Product, Architecture, TPM, and Data Governance teams to deliver secure, compliant, and high-quality data products. • Improve adoption of best practices in data engineering, including data quality, lineage, cataloging, and governance aligned with CDA and data mesh principles. • Champion agile methodologies and continuous improvement in engineering processes, tooling, and DevOps practices. • Cultivate engineering talent through coaching, career development, and performance management in a distributed team environment.

• Team Leadership & Mentorship: Lead and manage a small, agile team of software engineers. • DBT Testing & Quality Gates: Architect and implement a comprehensive testing suite within DBT. • Deep Data Analysis & Profiling: Perform exhaustive data profiling and deep-dive analyses using SQL and Python. • Product Strategy & Planning: Collaborate with Product Managers to develop and prioritize product backlog. • Modern Data Stack & Observability: Architect and implement observability frameworks using BigQuery, DBT, Elementary, and Grafana. • AI-Driven Development: Champion the use of AI productivity tools to streamline development.

• Lead, mentor, and empower a high-performing agile development team to deliver cutting-edge, end-to-end audio and video marketing solutions. • Bridge the gap between product strategy and technical execution, driving continuous delivery, optimizing team workflows, and fostering a culture of trust and technical excellence to support our growing subscription-based platform. • Perform One-on-Ones: Regular touchpoints focusing on career growth, unblocking issues, and building trust (not just project status updates). • Manage performance, set expectations, and deliver continuous feedback with formal performance reviews. • Handle team building, interviewing, onboarding new talent, and managing exits or performance improvement plans (PIPs). • Approve timesheets accurately and on time. • Partner with the team to ensure backlog is refined, estimated, and ready for successful sprint starts. • Facilitate continuous alignment and help the team reflect on improving processes during daily standups & retrospectives. • Represent the team's accomplishments and deliverables at end-of-sprint review meetings. • Track and report on team health and delivery performance (e.g., velocity, cycle time, burndown charts). • Collaborate with the Product Owner to align on product priorities, roadmap feasibility, and defining upcoming work. • Participate in architectural and design alignments with leaders across the backend, device, and in-reality teams to ensure technical cohesion. • Manage and resolve high-priority production issues and outages as the point person for production escalations. • Work with the Support team to triage, prioritize, and transition escalations from Zendesk into actionable Jira tickets.

• Lead, mentor, and manage a distributed engineering team across US and international time zones, fostering a culture of collaboration, accountability, and continuous improvement. • Partner closely with the CEO and Product Manager to translate business goals into clear, executable technical plans and sprint deliverables. • Own the full software development lifecycle — from planning and architecture to deployment and post-launch optimization. • Define and enforce coding standards, best practices, and architectural guidelines across the team to ensure high-quality, maintainable code. • Plan and manage sprint cycles using JIRA, coordinating task allocation, tracking progress, and removing blockers to keep delivery on schedule. • Oversee the team's use of GitHub for version control, code reviews, and CI/CD workflows, ensuring clean branching strategies and robust review processes. • Ensure all production systems are performant, reliable, and resource-efficient — actively monitoring and optimizing for cost, speed, and scalability. • Lead and contribute to the development, fine-tuning, and deployment of Generative AI models, working hands-on with LLMs and ML pipelines. • Continuously evaluate and adopt emerging technologies, frameworks, and AI advancements to keep auxi.ai's platform modern and competitive. • Coordinate cross-functional dependencies between engineering, product, and business stakeholders to ensure smooth execution. • Drive a culture of technical excellence, knowledge sharing, and innovation within the engineering organization.