Engineering Manager

About the Role

Your mission will be to transform GDP from a data mover to a decision engine. This involves building the 'Intelligence Layer', operationalizing high-value ML models, and pioneering the 'Harness Engineering' initiative. You will partner with Data Science to take predictive models out of the lab and into production, and drive the adoption of AI-native workflows.

The team you will be leading is responsible for managing the data infrastructure that drives Hinge Health's marketing efforts. Your technical expertise and leadership skills will be crucial in ensuring the success of this team and the company's growth strategy.

What You Will Do

• Build the 'Intelligence Layer': Move beyond simple data piping and architect the real-time decisioning layer that ingests ML signals and routes them instantly to execution platforms.
• Operationalize Growth ML Models: Partner with Data Science to take predictive models out of the lab and into production, owning the hardening, serving, and monitoring of models that control millions of dollars in marketing spend.
• Lead the Transition to Harness Engineering: Drive the adoption of AI-native workflows, shifting the team's focus from manual coding to building the test harnesses, specs, and safety rails that allow agents to autonomously maintain data pipelines.
• Guarantee Data Trust: Champion a culture of radical observability, implementing automated 'data sentinels' and contract tests that catch schema violations and freshness issues before they impact marketing campaigns.
• Collaborate with Cross-Functional Teams: Work closely with product, engineering, and data science teams to ensure alignment and effective execution of the company's growth strategy.
• Develop and Implement Data Engineering Technologies: Stay up-to-date with the latest data engineering technologies, including distributed data processing frameworks and SQL, and implement them to improve the efficiency and effectiveness of the team.
• Manage and Mentor Team Members: Provide guidance, support, and feedback to team members to help them grow professionally and technically.
• Ensure Data Quality and Integrity: Develop and implement processes to ensure the quality and integrity of the data, including data validation, data cleansing, and data normalization.
• Collaborate with Stakeholders: Work with stakeholders to understand their data needs and provide solutions that meet their requirements.
• Develop and Manage Data Pipelines: Design, develop, and manage data pipelines to ensure the efficient and effective flow of data across the organization.

What We Are Looking For

• 2+ years of experience managing engineering teams, with a proven track record of building and leading high-performing teams.
• 3+ years of experience with data engineering technologies, including distributed data processing frameworks and SQL.
• Experience with production data pipelines and understanding of data lifecycle management, including pipeline orchestration, monitoring, and operational excellence practices.
• Strong technical expertise, with the ability to dive deep into technical issues and provide guidance and support to team members.
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders.
• Experience with machine learning and data science, with the ability to understand and implement ML models and algorithms.
• Strong problem-solving skills, with the ability to analyze complex problems and develop effective solutions.
• Experience with Agile development methodologies and version control systems.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Nice to Have

• Experience with ML Ops and model serving, including experience with Kafka and event-driven architectures.
• Experience with AI-forward leadership, including experience with AI-native workflows and autonomous AI agents.
• Experience with architectural rigor, including experience with simplifying complex systems and converging sprawling pipeline patterns into robust standards.
• Experience with operational excellence, including experience with SLOs, runbooks, and incident management.
• Experience with marketing tech, including experience with Iterable, Braze, or similar platforms.

Benefits and Perks

• Competitive salary and benefits package.
• Opportunity to work with a leading health tech company and make a real impact on people's lives.
• Collaborative and dynamic work environment, with a team of experienced and dedicated professionals.
• Professional development opportunities, including training and education programs.
• Flexible working hours and remote work options.
• Access to the latest technologies and tools, including data engineering and machine learning platforms.
• Recognition and reward programs, including bonuses and stock options.
• Comprehensive health and wellness programs, including mental health support and employee assistance programs.

• When applying for this role, make sure to highlight your experience with data engineering technologies, including distributed data processing frameworks and SQL.
• Be prepared to discuss your experience with machine learning and data science, and how you have implemented ML models and algorithms in previous roles.
• Showcase your technical expertise and leadership skills, and provide examples of how you have built and led high-performing teams.
• Make sure to research the company and the role, and be prepared to discuss how you can contribute to the company's growth strategy.
• Consider including examples of your experience with AI-native workflows and autonomous AI agents, and how you have driven the adoption of these technologies in previous roles.
• Be prepared to discuss your experience with data quality and integrity, and how you have ensured the quality and integrity of data in previous roles.
• Highlight your excellent communication and collaboration skills, and provide examples of how you have worked effectively with cross-functional teams and stakeholders.