Senior Manager, Data Engineering
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Job Description
Sr. Manager leading data engineering team to optimize data infrastructure for insurance. Driving innovative data solutions and managing cross-functional collaborations within a remote setup.
Responsibilities:
- Manage a team of Data Engineers and Data Analytics Engineers owning our data infrastructure, including our medallion layers, data pipelines, and collaborating closely with MLEs on LLM Operations and agentic products.
- Navigate ambiguity, driving innovation through rapid prototyping and iterative development in cross-functional teams
- Partner with function leads and senior leadership to align growth paths, performance expectations, and strategic goals with technical excellence standards.
- Translate the Data Engineering vision into clear objectives, priorities, and milestones, ensuring effective project scoping, resourcing, and delivery.
- Define and refine agile workflows tailored to data engineering, managing key rituals such as design sessions, sprint planning, and retrospectives.
- Serve as the primary delivery interface across Product, Engineering, and Customer Success, ensuring alignment, transparent communication, and continuous improvement of team operations.
- Drive hiring excellence by attracting, developing, and scaling a high-performing team aligned with business needs.
Requirements:
- 8+ years of experience in data science, data engineering, or machine learning–related roles.
- 4+ years in a people management or delivery management role (directly leading technical contributors).
- Proven experience managing cross-functional ML technical teams and driving delivery across multiple workstreams.
- Strong understanding of data science lifecycle (from ideation and experimentation to deployment and maintenance).
- Practical experience with agile methodologies (Scrum, Kanban) and delivery facilitation.
- Excellent communication, organizational, and stakeholder management skills.
- Ability to balance technical depth with delivery discipline, ensuring outcomes, not just output.
- Experience with LLM Ops, agentic framework, data governance, and productionization best practices.
Benefits:
- stock options
- benefits and additional perks
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