Sr. Manager, Data Engineering

About this role

About Carrot:

Carrot is the leading global fertility and family care platform, built on intelligent care orchestration: the right clinical guidance, at the right moment, in the context of each member’s life. More than a thousand multinational employers, health plans, and health systems trust Carrot to support millions of members across 195 countries – from pre-pregnancy through menopause and major life moments in between. Carrot's comprehensive clinical program delivers industry-leading cost savings for plan sponsors and award-winning experiences and improved outcomes for millions of people worldwide.

Carrot is widely regarded as a defining force in healthcare innovation as a recipient of several top-tier awards, including Fast Company's 'Most Innovative Companies' and CNBC's '100 Barrier Breaking Startups'. The company is regularly cited by leading global outlets — including The Economist, Bloomberg, The Wall Street Journal, NPR, ABC News, and Harvard Business Review — as a leading voice on digital health, the future of work, and family health. Learn more at get-carrot.com .

The Opportunity 🚀

Carrot is seeking a Sr. Manager, Data Engineering to lead our Business Intelligence data engineering function as it scales to meet, and anticipate, the needs of the organization and its clients. This is a senior player/coach role with a strong emphasis on strategic leadership, technical excellence, and organizational impact. You will lead and grow a high-impact team while remaining deeply hands-on in architecting and building Carrot's data infrastructure.

You will set technical vision, drive cross-functional data strategy, and ensure our data systems are reliable, scalable, secure, and aligned with business priorities. You will influence and execute on the long-term roadmap for Data Engineering within the Data Team, defining how we ingest, transform, govern, and expose data across the company, and partner closely with senior leaders across Product, Engineering, Operations, Analytics, and Go-To-Market functions.

Given the small-but-mighty nature of the team, this role requires someone who is comfortable operating at multiple altitudes: setting multi-year architectural direction, shaping team and org design, and still rolling up their sleeves to build production-grade pipelines when needed.

What You’ll Own 💼

In this role, you will:

• Own the technical vision and roadmap for BI data engineering, aligning it with company strategy and analytics needs.

• Design, build, and review scalable ETL/ELT pipelines and workflow orchestration systems, contributing hands-on production code in Python and SQL .

• Architect and optimize data warehouse models that support advanced analytics, self-service BI, and operational reporting.

• Establish and enforce standards for reliability, observability, testing, and performance across all data systems.

• Drive improvements in data quality, lineage, and governance , including documentation and metadata practices.

• Partner with backend product engineering teams to co-design production database schemas and event models with analytics and reporting in mind.

• Lead, mentor, and develop a team of data engineers , fostering a culture of technical excellence, ownership, and collaboration.

• Own team-level planning and execution , including capacity planning, prioritization, and delivery across concurrent workstreams.

• Translate ambiguous business and analytics needs into a clear, prioritized engineering roadmap with measurable outcomes.

• Partner closely with Product, Engineering, Analytics, Security, and Legal to align on priorities, ensure compliance, and remove cross-functional blockers.

• Evaluate and influence build vs. buy decisions , vendor selection, and tool adoption across data platforms, ingestion, and transformation.

What Success Looks Like 📈

In your first 12–18 months, you will have:

• Elevated the maturity and consistency of data engineering practices across the BI function, with clear standards for reliability, testing, and observability.

• Built and retained a high-performing data engineering team recognized as a trusted partner to stakeholders across the business.

• Delivered a prioritized data engineering roadmap aligned with company strategy, with measurable progress on scalability and platform modernization.

• Strengthened the accuracy, recency, and security of enterprise data, meeting the requirements of regulated healthcare contexts.

• Enabled advanced analytics, self-service BI, and data products that drive meaningful business outcomes and influence Carrot's long-term data architecture strategy.

About You ✨

You likely have:

• 8-10+ years of experience in data engineering or a closely related field, including 3-5+ years leading and managing data or software engineers.

• 5+ years of advanced SQL and 5+ years of Python development experience in production environments, including unit and integration testing.

• Strong, hands-on experience designing, building, and maintaining end-to-end ETL/ELT pipelines in production.

• Proficiency with cloud-based data platforms (e.g., Snowflake, AWS) and modern ingestion, transformation, and orchestration tools (e.g., Fivetran, dbt, Prefect, Airflow).

• Strong understanding of relational modeling and warehouse design principles , plus version control (Git preferred) and modern CI/CD practices.

• Demonstrated ability to define technical strategy and standards while remaining capable of direct technical execution.

• Excellent written and verbal communication skills , with strong knowledge of data governance, security best practices, and compliance protocols.

Nice to Have ⭐

While not required, we would be especially excited if you bring:

• Direct experience with Carrot's current tech stack : Snowflake, Fivetran, dbt, Prefect, and AWS.

• Experience with enterprise BI platforms and enabling self-service analytics.

• Experience integrating batch and event-streaming or real-time ingestion

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