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Salary: USD 145,000 - 165,000 / annual
Carrot Fertility is seeking a Senior Data Engineer to lead the evolution, reliability, and scalability of the company's modern data infrastructure across analytics, reporting, and business intelligence. You will architect, build, and maintain robust, automated data pipelines, orchestrate workflows, integrate diverse data sources, and partner with stakeholders across the business 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. You will be an operational steward and technical mentor, driving improvements in system maturity, cost efficiency, automation, and collaborative practices.
Key responsibilities include:
- 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
In your first 12–18 months, you will take end-to-end ownership of core pipelines and integrations with measurable improvements in reliability, data recency, and cost efficiency. You will automate high-effort manual workflows, deliver secure and compliant data integrations that stakeholders trust for decision-making, strengthen observability across the platform, and establish yourself as a technical mentor and go-to partner for Business Intelligence, Product, and cross-functional teams.
Carrot is the leading global fertility and family care platform, built on intelligent care orchestration. More than a thousand multinational employers, health plans, and health systems trust Carrot to support millions of members across 195 countries. The company has received recognition including Fast Company's Most Innovative Companies and CNBC's 100 Barrier Breaking Startups.
REQUIREMENTS:
- 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
- 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
- Demonstrated ability to automate and simplify complex manual tasks, building robust, reusable pipeline components
- Dependability, adaptability, and collaborative approach to engineering, thriving in dynamic and ambiguous environments
NICE TO HAVE:
- Hands-on experience in startup or rapid-growth environments, delivering technical solutions under shifting priorities
- 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
