Senior Manager of Data Engineering, Carrot Fertility

• 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
• 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

Desirable

• 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
• 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
• The reliability, scalability, and usability of Carrot's data systems directly power decision-making across the organization and for our clients. Data Engineering plays a foundational role in enabling the broader Business Intelligence function, and this role serves as the senior-most manager directly responsible for that capability
• The Business Intelligence team at Carrot is highly cross-functional and central to the company's long-term success. Led by our Vice President of Data and Business Intelligence, the team includes data engineers, data scientists, and business intelligence analysts. In this role, you will build and nurture a high-performing team, ensure the accuracy and security of enterprise data in a regulated healthcare context, and influence the long-term data architecture and platform strategy at Carrot

• Recruiter Screen — 30 minutes
• Hiring Manager Interview — 30–45 minutes
• Cross-Functional Panel Interviews — 45 minutes
• Executive Leadership Conversation — 30 minutes
• Hiring Manager Wrap-Up — 15 minutes
• Throughout the process, we will share additional context about the team, business priorities, customer landscape, and what success looks like in this role