[![Image]() Meet Jobicy Copilot — free AI autofill for job applications + remote job alerts ›](#) [All remote jobs](https://jobicy.com/jobs.md)Open role[![Carrot logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2021/07/005d05de29487ec44cd07bd9d757d4e1.png)](https://jobicy.com/company/carrot.md)Remote opportunity at[Carrot](https://jobicy.com/company/carrot.md) # Sr. Data Engineer Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/carrot.md)Share18 Sep 2026Published31Listing views2Application actions18 Oct 2026Apply before Opportunity details ## About this role. AI SummaryCarrot is hiring a Senior Data Engineer to own the reliability, scalability, and governance of its data platform supporting analytics, reporting, and business intelligence. The role designs and operates ETL/ELT pipelines, cloud data warehouses and lakes, workflow orchestration, and secure external integrations. It requires deep hands-on expertise with Snowflake, dbt, Python, SQL, Airflow or Prefect, AWS, and Google Cloud. The engineer will automate reporting workflows, improve observability and cost efficiency, mentor teammates, and collaborate with Product, BI, Finance, Legal, and Commercial stakeholders. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a senior-level platform role requiring architecture ownership across complex, regulated data systems as well as advanced hands-on engineering skills. The role also carries operational accountability for data reliability, security, governance, and cross-functional delivery in a fast-growth environment. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianMarket rate$155,000US market range$140k–$190k0$209k AI insightThe disclosed base-salary range is $145,000 to $165,000 USD per year, producing an offer median of $155,000. For a US-based Senior Data Engineer with Snowflake, dbt, cloud warehouse, orchestration, and data-governance expertise, a competitive estimated market base range is approximately $140,000 to $190,000 USD annually; total compensation may be higher with equity and incentives. ## Core skills Skills and capabilities most closely associated with this opportunity. [Data Engineering](https://jobicy.com/jobs?search_keywords=Data%20Engineering.md)[ETL/ELT](https://jobicy.com/jobs?search_keywords=ETLELT.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Snowflake](https://jobicy.com/jobs?search_keywords=Snowflake.md)[dbt](https://jobicy.com/jobs?search_keywords=dbt.md)[Apache Airflow](https://jobicy.com/jobs?search_keywords=Apache%20Airflow.md)[Prefect](https://jobicy.com/jobs?search_keywords=Prefect.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[Data Governance](https://jobicy.com/jobs?search_keywords=Data%20Governance.md) Sample interview questionsHow would you design a resilient ETL/ELT pipeline for a high-volume external data source?I would begin by defining the source contract, freshness expectations, schema-evolution strategy, and failure modes. I would build idempotent ingestion with durable raw storage, validation checks, retries, alerting, lineage, and staged dbt transformations so data can be replayed safely. I would also establish SLAs and dashboards for completeness, latency, and quality. What approaches do you use to improve Snowflake performance and manage cost? I analyze query profiles, warehouse utilization, data-volume trends, and workload patterns before tuning. Typical actions include right-sizing warehouses, configuring auto-suspend and auto-resume, improving partition-pruning behavior, reducing unnecessary scans, using incremental models, and separating compute workloads. I pair technical changes with cost observability so teams can measure the impact over time. How do you implement data quality and governance in a regulated environment? I treat governance as part of the engineering lifecycle by documenting ownership, lineage, classification, access policies, and retention requirements. I implement automated tests for schema, freshness, uniqueness, referential integrity, and business rules, while enforcing least-privilege access and audited changes. For sensitive healthcare-related data, I would partner closely with legal and security teams to align controls with applicable privacy obligations. Describe how you would migrate a manual reporting process into an automated solution. I would first map the current inputs, transformations, business definitions, owners, and recurring failure points. Then I would model the logic in version-controlled transformations, schedule the workflow through an orchestrator, add tests and monitoring, and publish a documented self-service output. I would run the automated result in parallel with the manual process until accuracy and stakeholder confidence are established. How do you mentor engineers while maintaining high operational standards? I use code reviews, pairing, architecture discussions, and clear runbooks to make best practices repeatable rather than dependent on one person. I encourage small, observable changes with strong testing and post-incident learning. I also give teammates ownership of meaningful systems while remaining available to unblock decisions and reinforce reliability, security, and documentation standards. About Carrot: [Carrot](https://c212.net/c/link/?t=0&l=en&o=4420559-1&h=3535232987&u=https%3A%2F%2Fwww.carrotfertility.com%2F&a=Carrot+Fertility) 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](http://get-carrot.com). The Opportunity 🚀 Carrot is seeking a Sr. Data Engineer to lead the evolution, reliability, and scalability of our modern data infrastructure across analytics, reporting, and business intelligence. In this role, 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. 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 our 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 to deliver reliable integrations and self-serve solutions that drive business insights and operational efficiency. What You’ll Own 💼 In this role, you will: * 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 📈 In your first 12–18 months, you will have: * Taken end-to-end ownership of core pipelines and integrations, with measurable improvements in reliability, data recency, and cost efficiency * Automated high-effort manual workflows, reducing operational risk and freeing capacity for higher-value engineering work * Delivered secure, compliant data integrations that stakeholders across the business trust for decision-making * Strengthened observability across the platform, including monitoring, alerting, and incident response for critical data workflows * Established yourself as a technical mentor and a go-to partner for Business Intelligence, Product, and cross-functional teams About You ✨ You likely have: * 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 ⭐ While not required, we would be especially excited if you bring: * Hands-on experience in startup or rapid-growth environments, delivering technical solutions under shifting priorities * 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 our data platform more automated, resilient, and cost-efficient, enabling teams across the business to move faster with data they trust. This work directly supports Carrot’s mission of expanding access to fertility and family-building care worldwide. Interview Process 🤝 We believe in a thoughtful and transparent interview process designed to create alignment for both candidates and our team. For this role, candidates can expect: * 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. ### Why Candidates Join Carrot 🌍 Carrot offers the opportunity to do meaningful work in service of a deeply human mission. Highlights include: * A mission-driven company focused on expanding access to fertility and family-forming care globally. * A high-growth environment where leaders are empowered to shape strategy and drive impact. * Competitive compensation, equity, and comprehensive benefits. * Flexible Time Off and a culture that actively encourages employees to recharge. * Comprehensive parental leave and family-forming benefits. * A collaborative, inclusive, and values-driven culture. * The opportunity to work alongside passionate, thoughtful teammates committed to improving healthcare outcomes worldwide. Compensation: Carrot offers a holistic Total Rewards package designed to support our employees in all aspects of their life inside and outside of work, including health and wellness benefits, retirement savings plans, short- and long-term incentives, parental leave, family-forming assistance, and a competitive compensation package. The starting base salary for this position will range from $145,000-$165,000. Actual compensation may vary from posted base salary depending on your confirmed job-related skills and experience. Fraud and Security Notice: Please note that all communication regarding job opportunities at Carrot will come exclusively from an @get-carrot.com email address. If you receive messages from any other domain, please disregard them and report the incident to: [securityreporting@get-carrot.com](mailto:securityreporting@get-carrot.com) A Note on AI At Carrot, we believe AI can help us work smarter, move faster, and create more meaningful experiences for our members, customers, and each other. While not every role requires deep technical AI expertise, we value people who are curious, eager to learn, and excited to thoughtfully incorporate AI into their day-to-day work. For some roles, AI fluency is a core requirement—and we’ll call that out clearly in the qualifications. For everyone else, we’re looking for people who embrace new ways of working, use AI responsibly to improve quality and efficiency, and continue to learn as the technology evolves. Why Carrot? Carrot has received national and international recognition for its pioneering work, including Fast Company’s Most Innovative Companies and World Changing Ideas, Inc. Power Partners, and Modern Healthcare’s Innovators. Carrot’s global workforce has been acknowledged with several accolades, including Fortune’s Best Workplaces in Healthcare, Great Place to Work, and Age-Friendly Employer certifications. Carrot is regularly featured in media reporting on issues related to the future of work, women in leadership, and healthcare innovation, including MSNBC, The Economist, Bloomberg, The Wall Street Journal, CNBC, National Public Radio, Harvard Business Review, and more. Learn more at carrotfertility.com. 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