Data Engineering Manager, Philo

• 10+ years of professional experience in data engineering, ideally with a few years working on high-volume data platforms
• 2+ years of experience managing data engineering teams in cloud-native environments
• Deep expertise in modern data stack technologies, particularly AWS data services, Snowflake, dbt, Airflow, Airbyte, Python, and SQL
• Strong people management skills with experience providing coaching, performance feedback, and career development guidance to direct reports
• Strong track record of designing and implementing data platforms
• Excellent communication skills with technical and non-technical stakeholders, simplifying complex data concepts for various business audiences
• Experience managing cloud-based data platforms (AWS/GCP/Azure)

Desirable

• We're seeking an experienced Data Engineering Manager to join our team at Philo
• Engineering Managers at Philo lead by example, and are expected to write code and demonstrate best practices while also providing coaching, technical leadership, and insights within and across teams
• We expect an even split between hands-on technical work (designing, architecting, and implementing our long-term data platform strategy) and people management (coaching, mentoring, and developing a high-performing data engineering team)
• The ideal candidate is strongly opinionated about data stack architecture and how to enhance velocity across the entire Data Team at Philo
• Drive technical leadership to members of the Data Engineering team, including input on data pipeline design, performance optimization, and AWS cloud services, as well as coaching team members and mentoring new hires
• Provide strong people management for the team, including regular 1:1 meetings, career development guidance, and general check-ins to support individual growth and team morale
• Lead the design and implementation of Philo's data platform architecture
• Set technical standards and best practices for data engineering work
• Collaborate with cross-functional teams to understand data platform needs and translate business requirements into technical solutions
• Design scalable data pipelines and infrastructure
• Manage team workload, priorities, and delivery timelines
• Implement data governance, security, and quality control processes
• Drive technical decisions with a focus on long-term sustainability