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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** AIR FLOW, INC. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $113,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** Airflow, Data Analysis, Automation of Tests, Big Data, BigQuery, Continuous Delivery, Data as a Services, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Systems, Monitoring of Systems, Operational Databases, Software Deployment, Datadog, Delivery Pipeline, Indexer, Kubernetes, Data Management, Data Pipelines - **Published:** July 5, 2026 - **Apply:** https://jobs.gem.com/apartment-list/am9icG9zdDoimfAg9d54CIyL9evKu0-T ## About the Role * 5+ years of experience in data engineering, with a track record of delivering reliable production data pipelines and systems. * Strong experience designing and maintaining orchestration workflows using Apache Airflow. * Experience building scalable data pipelines using modern cloud data platforms such as BigQuery and tools such as DBT. * Strong understanding of data modeling, schema design, and building maintainable, modular data systems. * Experience implementing CI/CD best practices for data pipelines, including automated testing, validation, and deployment workflows to ensure reliable and repeatable production releases. * Experience monitoring and operating production data systems, including pipeline observability, data quality checks, and incident response. * Ability to identify performance and cost risks in large-scale data systems and implement optimizations. * Strong collaboration skills and experience working with cross-functional partners including analytics engineers, data scientists, and product teams. * Proven ability to independently execute medium-sized projects and deliver reliable, production-grade systems. Nice-to-haves * Familiarity with Kubernetes-based data infrastructure, including deploying and operating containerized data services and workflows in a production environment. * Experience migrating legacy ETL systems to modern orchestration frameworks. * Familiarity with observability and monitoring tools for data pipelines (e.g., Datadog or similar). * Experience operating data systems with strict SLAs for freshness, reliability, and cost efficiency. ## Description We are seeking a Senior Data Engineer (L3) to help build and operate the reliable, scalable data systems that power analytics, experimentation, and decision-making across Apartment List. In this role, you will be a strong end-to-end executor responsible for delivering production-grade data pipelines and workflows that meet defined service-level agreements (SLAs) for freshness, quality, and cost. You will work closely with Analytics Engineering, Data Science, Product, and Engineering partners to deliver durable data platform improvements that support company-wide initiatives. The ideal candidate is comfortable owning medium-sized data platform projects end-to-end-from design through deployment and operational support-while working within established platform architecture and engineering patterns. This role emphasizes execution excellence, reliability, and operational ownership within existing platform standards. Platform-level architecture and system design are owned at more senior levels, but this role plays a critical part in ensuring that the platform functions reliably at scale. Responsibilities * Design, build, test, and deploy scalable and reliable data pipelines that power analytics and product decision-making. * Own medium-sized data platform initiatives end-to-end, from initial design through production deployment and operational support. * Design, migrate, and maintain data workflows in Apache Airflow, including supporting migration of legacy ETL systems to modern orchestration patterns. * Ensure pipeline reliability by proactively monitoring workflow SLAs for freshness, quality, and performance, and resolving failures efficiently. * Implement and utilize monitoring systems to detect pipeline failures, schema drift, and data quality anomalies. * Participate in on-call rotations and contribute to incident response and root cause analysis for data incidents. * Apply best practices in warehouse performance and cost optimization, including partitioning, indexing, and efficient data modeling to control BigQuery spend. * Build maintainable, modular data models and pipelines using reusable patterns and shared components across the team. * Partner closely with Analytics Engineering, Data Science, and business stakeholders to deliver durable improvements across the ingestion, transformation, modeling, and serving layers of the data platform. * Contribute to operational excellence through documentation, monitoring improvements, and participation in postmortems and reliability initiatives. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Optimizing Discovery: PostgreSQL's Role in Transforming GetYourGuide's Search](https://www.wearedevelopers.com/videos/1647-optimizing-discovery-postgresql-s-role-in-transforming-getyourguide-s-search) - [The OpenTelemetry mistakes I keep seeing (and how to stop making them)](https://www.wearedevelopers.com/videos/100158-the-opentelemetry-mistakes-i-keep-seeing-and-how-to-stop-making-them) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Dynamic Entities in .NET: Building Low-Code Systems on Top of Entity Framework Core](https://www.wearedevelopers.com/videos/100218-dynamic-entities-in-net-building-low-code-systems-on-top-of-entity-framework-core) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [DevOps Engineer Salary [2023]](https://www.wearedevelopers.com/magazine/203-devops-engineer-salary-2023) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Why Event-Driven Architecture Isn’t About Speed (and When You Actually Need It)](https://www.wearedevelopers.com/magazine/745-why-event-driven-architecture-isn-t-about-speed-and-when-you-actually-need-it)