Sr. Data Engineer

About Carrot: Carrot is the leading global fertility and family care platform, built on intelligent care orchestration. Over 1,000 multinational employers, health plans, and health systems trust Carrot to support millions of members across 195 countries.

The Opportunity 🚀: Carrot is seeking a Sr. Data Engineer to lead the evolution, reliability, and scalability of its modern data infrastructure across analytics, reporting, and business intelligence. This role involves architecting, building, and maintaining robust, automated data pipelines, orchestrating workflows, integrating diverse data sources, and partnering with stakeholders to deliver secure, compliant, high-quality data solutions.

Your work will span the full data lifecycle, from architecting resilient ETL/ELT pipelines and developing real-time and batch data integrations to automating reporting, reducing technical debt, and enabling advanced analytics. Sr. Data Engineers at Carrot are operational stewards and technical mentors, driving improvements in system maturity, cost efficiency, automation, and collaborative practices.

You will join the Data Engineering team, which develops and optimizes scalable data pipelines and cloud infrastructure to enable secure, automated reporting and analytics across Carrot. The team collaborates closely with Business Intelligence, Product, Finance, Legal, and Commercial partners.

What You’ll Own 💼:

• Architect, build, test, deploy, and maintain scalable, automated ETL/ELT pipelines using Python, dbt, and orchestration tools such as Prefect and Airflow
• Administer and optimize cloud-based data warehouse and lake platforms, including Snowflake, AWS (S3, Redshift), and Google Cloud, integrating new sources and tuning for performance and cost
• Orchestrate data workflows with custom scheduling, alerting, dependency management, monitoring, and error resolution
• Design and maintain secure external data flows through SFTP, Files.com, and APIs, with a focus on reliability and compliance
• Automate manual reporting and operational tasks, building robust, reusable pipeline components that reduce operational overhead
• Partner with backend product engineers to optimize production database schemas with analytics use cases in mind
• Strengthen data quality, lineage, governance, and documentation practices across key data domains
• Mentor teammates and reinforce best practices in version control, code review, and structured workflow management

What Success Looks Like 📈:

• Take end-to-end ownership of core pipelines and integrations, with measurable improvements in reliability, data recency, and cost efficiency within 12–18 months
• Automate high-effort manual workflows, reducing operational risk and freeing capacity for higher-value engineering work
• Deliver secure, compliant data integrations that stakeholders across the business trust for decision-making
• Strengthen observability across the platform, including monitoring, alerting, and incident response for critical data workflows
• Establish yourself as a technical mentor and a go-to partner for Business Intelligence, Product, and cross-functional teams

About You ✨:

• Expert-level proficiency in Snowflake, dbt, and Python for data modeling, transformation, pipeline development, and advanced analytics
• Advanced SQL skills for complex querying, large-scale data model design, and database optimization
• Proven experience architecting, building, testing, deploying, and maintaining scalable, automated ETL/ELT pipelines using modern orchestration tools such as Prefect and Airflow
• Hands-on administration of cloud-based data warehouse and lake platforms, including Snowflake, AWS (S3, Redshift), and Google Cloud
• A strong understanding of secure external data flows through SFTP, Files.com, and APIs, with a focus on reliability and compliance
• Mastery of version control (Git, GitHub) and structured workflow management (Jira) for code review, audit trails, and operational transparency
• A demonstrated ability to automate and simplify complex manual tasks, building robust, reusable pipeline components
• Dependability, adaptability, and a collaborative approach to engineering, thriving in dynamic and ambiguous environments

Nice to Have ⭐:

• Hands-on experience in startup or rapid-growth environments
• A background supporting business intelligence, analytics, and data science teams through large-scale integrations and multi-tenant reporting
• Familiarity with both batch and event-driven ingestion paradigms, including near-real-time pipelines built on Snowflake, dbt, and Python
• Experience automating operational, financial, or compliance-driven workflows within cloud data environments
• Exposure to audit, privacy, and compliance frameworks such as SOC 2, HIPAA, GDPR, ISO, and SOX, particularly in data governance and secure access controls
• Experience in regulated industries such as healthcare, healthtech, or SaaS

Why This Role Matters 🧡:

Reliable data is the foundation of how Carrot operates, from the analytics that guide business decisions to the reporting our customers and partners depend on. The systems this role owns determine the accuracy, recency, and security of data used across the entire company.

As Carrot scales globally, the Sr. Data Engineer will make the data platform more automated, resilient, and cost-efficient, enabling teams across the business to move faster with data they trust.